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MEANS User Documentation

MEANS is an acronym for the MIT Extensible Air Network Simulation. MIT is the Massachusetts Institute of Technology, where MEANS was developed. MEANS models the flow of aircraft in a simulation of the US National Airspace System. It can optionally follow the flow of passengers as well. The flight model takes the form of several queues through which the aircraft pass, as well as delays at certain times; the passengers can be transported via flights. MEANS is an event-based model. This means that events are scheduled at some point in the future, and once an event has executed, the simulation t h e advances to that of the next event. This is a different approach than some simulations (particularly those of physical systems), where time is advanced in fixed increments and the state of the system is updated at each step.This documentation is a "user guide" for MEANS - it describes how to USE means, not write new modules. For programming instructions, see the programming documentation, available as a separate document.This document assumse no programming knowledge. It will describe how to run MEANS, understand the data formats, and use such utility programs as already exist. For more detailed information on the internal workings of MEANS, and how to programmatically add to it, refer to the programming documentation.

Melconian, Terran↗

An Introduction to Thermodynamic Performance Analysis of Aircraft Gas Turbine Engine Cycles Using the Numerical Propulsion System Simulation Code

This document is intended as an introduction to the analysis of gas turbine engine cycles using the Numerical Propulsion System Simulation (NPSS) code. It is assumed that the analyst has a firm understanding of fluid flow, gas dynamics, thermodynamics, and turbomachinery theory. The purpose of this paper is to provide for the novice the information necessary to begin cycle analysis using NPSS. This paper and the annotated example serve as a starting point and by no means cover the entire range of information and experience necessary for engine performance simulation. NPSS syntax is presented but for a more detailed explanation of the code the user is referred to the NPSS User Guide and Reference document (ref. 1).

Jones, Scott M.↗

Anvil Tool in the Advanced Weather Interactive Processing System

Meteorologists from the 45th Weather Squadron (45 WS) and Spaceflight Meteorology Group (SMG) have identified anvil forecasting as one of their most challenging tasks when predicting the probability of violations of the lightning Launch Commit Criteria and Space Shuttle Flight Rules. As a result, the Applied Meteorology Unit (AMU) created a graphical overlay tool for the Meteorological Interactive Data Display Systems (MIDDS) to indicate the threat of thunderstorm anvil clouds, using either observed or model forecast winds as input. In order for the Anvil Tool to remain available to the meteorologists, the AMU was tasked to transition the tool to the Advanced Weather interactive Processing System (AWIPS). This report describes the work done by the AMU to develop the Anvil Tool for AWIPS to create a graphical overlay depicting the threat from thunderstorm anvil clouds. The AWIPS Anvil Tool is based on the previously deployed AMU MIDDS Anvil Tool. SMG and 45 WS forecasters have used the MIDDS Anvil Tool during launch and landing operations. SMG's primary weather analysis and display system is now AWIPS and the 45 WS has plans to replace MIDDS with AWIPS. The Anvil Tool creates a graphic that users can overlay on satellite or radar imagery to depict the potential location of thunderstorm anvils one, two, and three hours into the future. The locations are based on an average of the upper-level observed or forecasted winds. The graphic includes 10 and 20 nm standoff circles centered at the location of interest, in addition to one-, two-, and three-hour arcs in the upwind direction. The arcs extend outward across a 30 degree sector width based on a previous AMU study which determined thunderstorm anvils move in a direction plus or minus 15 degrees of the upper-level (300- to 150-mb) wind direction. This report briefly describes the history of the MIDDS Anvil Tool and then explains how the initial development of the AWIPS Anvil Tool was carried out. After testing was performed by SMG, 45 WS, and AMU, a number of needed improvements were identified. A bug report document was created that showed the status of each bug and desired improvement. This report lists the improvements that were made to increase the accuracy and user-friendliness of the tool. Final testing was carried out and documented and then the final version of the software and Users Guide was provided to SMG and the 45 WS. Several possible future improvements to the tool are identified that would increase the flexibility of the tool. This report contains a brief history of the development of the Anvil Tool in MIDDS, and then describes the transition and development of software to AWIPS.

Barrett, Joe, III↗

The New Landsat Image Mosaic of Antarctica; A Part of Your World You've Never Seen Before

The first-ever true-color, high-resolution digital mosaic of Antarctica has been produced from nearly 11 00 Landsat-7 ETM+ images. This project is an early 1999-2001 benchmark data set of the International Polar Year and represents a close and successful collaboration between NASA, USGS, the British Antarctic Survey and the National Science Foundation. The production of the mosaic required the development of new procedures for treating sensor saturation, adjusting for non-diffusive reflectance and for balancing color between images to remove distracting image edges. All adjustments were physically based to achieve the goal that each pixel's value is surface reflectance. This makes this mosaic more than just a pretty picture to guide users to individual scenes, but one where the mosaics can be used directly for quantitative research. The 15-m resolution, pan-sharpened mosaic, numerous derivative mosaics that enhance various ice sheet features, and the individual scenes are all served to the public via a web site hosted by the USGS. This site also enables on-line exploration of the various mosaics, including panning and zooming functions. Datasets can be customized by the user and downloaded. An associated web site, hosted by NASA, uses the mosaic as a means to demonstrate the value of satellite imagery of Antarctica. It is hoped this data set will enable the public and researcher alike a new and realistic view of the seventh continent.

Bindschadler, Robert↗

Prediction of Spacecraft Vibration using Acceleration and Force Envelopes

The base forces in the GLAST X- and Z-axis sine vibration tests were similar to those derived using generic inputs (from users guide and handbook), but the base forces in the sine test were generally greater than the flight data. Basedrive analyses using envelopes of flight acceleration data provided more accurate predictions of the base force than generic inputs, and as expected, using envelopes of both the flight acceleration and force provided even more accurate predictions The GLAST spacecraft interface accelerations and forces measured during the MECO transient were relatively low in the 60 to 150 Hz regime. One may expect the flight forces measured at the base of various spacecraft to be more dependent on the mass, frequencies, etc. of the spacecraft than are the corresponding interface acceleration data, which may depend more on the launch vehicle configuration.

Gordon, Scott↗

Complexity Management Using Metrics for Trajectory Flexibility Preservation and Constraint Minimization

The growing demand for air travel is increasing the need for mitigating air traffic congestion and complexity problems, which are already at high levels. At the same time new surveillance, navigation, and communication technologies are enabling major transformations in the air traffic management system, including net-based information sharing and collaboration, performance-based access to airspace resources, and trajectory-based rather than clearance-based operations. The new system will feature different schemes for allocating tasks and responsibilities between the ground and airborne agents and between the human and automation, with potential capacity and cost benefits. Therefore, complexity management requires new metrics and methods that can support these new schemes. This paper presents metrics and methods for preserving trajectory flexibility that have been proposed to support a trajectory-based approach for complexity management by airborne or ground-based systems. It presents extensions to these metrics as well as to the initial research conducted to investigate the hypothesis that using these metrics to guide user and service provider actions will naturally mitigate traffic complexity. The analysis showed promising results in that: (1) Trajectory flexibility preservation mitigated traffic complexity as indicated by inducing self-organization in the traffic patterns and lowering traffic complexity indicators such as dynamic density and traffic entropy. (2)Trajectory flexibility preservation reduced the potential for secondary conflicts in separation assurance. (3) Trajectory flexibility metrics showed potential application to support user and service provider negotiations for minimizing the constraints imposed on trajectories without jeopardizing their objectives.

Idris, Husni↗

NASA Near Earth Network (NEN), Deep Space Network (DSN) and Space Network (SN) Support of CubeSat Communications

There has been a historical trend to increase capability and drive down the Size, Weight and Power (SWAP) of satellites and that trend continues today. Small satellites, including systems conforming to the CubeSat specification, because of their low launch and development costs, are enabling new concepts and capabilities for science investigations across multiple fields of interest to NASA. NASA scientists and engineers across many of NASAs Mission Directorates and Centers are developing exciting CubeSat concepts and welcome potential partnerships for CubeSat endeavors. From a communications and tracking point of view, small satellites including CubeSats are a challenge to coordinate because of existing small spacecraft constraints, such as limited SWAP and attitude control, low power, and the potential for high numbers of operational spacecraft. The NASA Space Communications and Navigation (SCaN) Programs Near Earth Network (NEN), Deep Space Network (DSN) and the Space Network (SN) are customer driven organizations that provide comprehensive communications services for space assets including data transport between a missions orbiting satellite and its Mission Operations Center (MOC). The NASA NEN consists of multiple ground antennas. The SN consists of a constellation of geosynchronous (Earth orbiting) relay satellites, named the Tracking and Data Relay Satellite System (TDRSS). The DSN currently makes available 13 antennas at its three tracking stations located around the world for interplanetary communication. The presentation will analyze how well these space communication networks are positioned to support the emerging small satellite and CubeSat market. Recognizing the potential support, the presentation will review the basic capabilities of the NEN, DSN and SN in the context of small satellites and will present information about NEN, DSN and SN-compatible flight radios and antenna development activities at the Goddard Space Flight Center (GSFC) and across industry. The presentation will review concepts on how the SN multiple access capability could help locate CubeSats and provide a low-latency early warning system. The presentation will also present how the DSN is evolving to maximize use of its assets for interplanetary CubeSats. The critical spectrum-related topics of available and appropriate frequency bands, licensing, and coordination will be reviewed. Other key considerations, such as standardization of radio frequency interfaces and flight and ground communications hardware systems, will be addressed as such standardization may reduce the amount of time and cost required to obtain frequency authorization and perform compatibility and end-to-end testing. Examples of standardization that exist today are the NASA NEN, DSN and SN systems which have published users guides and defined frequency bands for high data rate communication, as well as conformance to CCSDS standards. The workshop session will also seek input from the workshop participants to better understand the needs of small satellite systems and to identify key development activities and operational approaches necessary to enhance communication and navigation support using NASA's NEN, DSN and SN.

Telecommunication↗

Global Precipitation Measurement (GPM) Mission Products and Services at the NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC)

On February 27, 2014, the NASA Global Precipitation Measurement (GPM) mission was launched to provide the next-generation global observations of rain and snow (http:pmm.nasa.govGPM). The GPM mission consists of an international network of satellites in which a GPM Core Observatory satellite carries both active and passive microwave instruments to measure precipitation and serve as a reference standard, to unify precipitation measurements from a constellation of other research and operational satellites. The NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) hosts and distributes GPM data within the NASA Earth Observation System Data Information System (EOSDIS). The GES DISC is home to the data archive for the GPM predecessor, the Tropical Rainfall Measuring Mission (TRMM). Over the past 16 years, the GES DISC has served the scientific as well as other communities with TRMM data and user-friendly services. During the GPM era, the GES DISC will continue to provide user-friendly data services and customer support to users around the world. GPM products currently and to-be available include the following: 1. Level-1 GPM Microwave Imager (GMI) and partner radiometer products. 2. Goddard Profiling Algorithm (GPROF) GMI and partner products. 3. Integrated Multi-satellitE Retrievals for GPM (IMERG) products. (early, late, and final)A dedicated Web portal (including user guides, etc.) has been developed for GPM data (http:disc.sci.gsfc.nasa.govgpm). Data services that are currently and to-be available include Google-like Mirador (http:mirador.gsfc.nasa.gov) for data search and access; data access through various Web services (e.g., OPeNDAP, GDS, WMS, WCS); conversion into various formats (e.g., netCDF, HDF, KML (for Google Earth), ASCII); exploration, visualization, and statistical online analysis through Giovanni (http:giovanni.gsfc.nasa.gov); generation of value-added products; parameter and spatial subsetting; time aggregation; regridding; data version control and provenance; documentation; science support for proper data usage, FAQ, help desk; monitoring services (e.g. Current Conditions) for applications.In this presentation, we will present GPM data products and services with examples.

NASA GES DISC↗

Global Precipitation Measurement (GPM) Mission Products and Services at the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC)

On February 27, 2014, the NASA Global Precipitation Measurement (GPM) mission was launched to provide the next-generation global observations of rain and snow (http:pmm.nasa.govGPM). The GPM mission consists of an international network of satellites in which a GPM Core Observatory satellite carries both active and passive microwave instruments to measure precipitation and serve as a reference standard, to unify precipitation measurements from a constellation of other research and operational satellites. The NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) hosts and distributes GPM data within the NASA Earth Observation System Data Information System (EOSDIS). The GES DISC is home to the data archive for the GPM predecessor, the Tropical Rainfall Measuring Mission (TRMM). Over the past 16 years, the GES DISC has served the scientific as well as other communities with TRMM data and user-friendly services. During the GPM era, the GES DISC will continue to provide user-friendly data services and customer support to users around the world. GPM products currently and to-be available include the following:Level-1 GPM Microwave Imager (GMI) and partner radiometer productsLevel-2 Goddard Profiling Algorithm (GPROF) GMI and partner productsLevel-3 daily and monthly productsIntegrated Multi-satellitE Retrievals for GPM (IMERG) products (early, late, and final) A dedicated Web portal (including user guides, etc.) has been developed for GPM data (http:disc.sci.gsfc.nasa.govgpm). Data services that are currently and to-be available include Google-like Mirador (http:mirador.gsfc.nasa.gov) for data search and access; data access through various Web services (e.g., OPeNDAP, GDS, WMS, WCS); conversion into various formats (e.g., netCDF, HDF, KML (for Google Earth), ASCII); exploration, visualization, and statistical online analysis through Giovanni (http:giovanni.gsfc.nasa.gov); generation of value-added products; parameter and spatial subsetting; time aggregation; regridding; data version control and provenance; documentation; science support for proper data usage, FAQ, help desk; monitoring services (e.g. Current Conditions) for applications.

precipitation↗

Using the General Mission Analysis Tool (GMAT)

This is a software tutorial and presentation demonstrating the application of the General Mission Analysis Tool (GMAT). These slides will be used to accompany the demonstration. The demonstration discusses GMAT basics, then presents a detailed example of GMAT application to the Transiting Exoplanet Survey Satellite (TESS) mission. This talk is a combination of existing presentations and material; system user guide and technical documentation; a GMAT basics and overview, and technical presentations from the TESS projects on their application of GMAT to critical mission design. The GMAT basics slides are taken from the open source training material. The TESS slides are a streamlined version of the CDR package provided by the project with SBU and ITAR data removed by the TESS project. Slides for navigation and optimal control are borrowed from system documentation and training material.

trajectory↗

Expansion of Tabulated Scattering Matrices in Generalized Spherical Functions

An efficient way to solve the vector radiative transfer equation for plane-parallel turbid media is to Fourier-decompose it in azimuth. This methodology is typically based on the analytical computation of the Fourier components of the phase matrix and is predicated on the knowledge of the coefficients appearing in the expansion of the normalized scattering matrix in generalized spherical functions. Quite often the expansion coefficients have to be determined from tabulated values of the scattering matrix obtained from measurements or calculated by solving the Maxwell equations. In such cases one needs an efficient and accurate computer procedure converting a tabulated scattering matrix into the corresponding set of expansion coefficients. This short communication summarizes the theoretical basis of this procedure and serves as the user guide to a simple public-domain FORTRAN program.

scattering matrix↗

Agile Multi-Scale Decompositions for Automatic Image Registration

In recent works, the first and third authors developed an automatic image registration algorithm based on a multiscale hybrid image decomposition with anisotropic shearlets and isotropic wavelets. This prototype showed strong performance, improving robustness over registration with wavelets alone. However, this method imposed a strict hierarchy on the order in which shearlet and wavelet features were used in the registration process, and also involved an unintegrated mixture of MATLAB and C code. In this paper, we introduce a more agile model for generating features, in which a flexible and user-guided mix of shearlet and wavelet features are computed. Compared to the previous prototype, this method introduces a flexibility to the order in which shearlet and wavelet features are used in the registration process. Moreover, the present algorithm is now fully coded in C, making it more efficient and portable than the MATLAB and C prototype. We demonstrate the versatility and computational efficiency of this approach by performing registration experiments with the fully-integrated C algorithm. In particular, meaningful timing studies can now be performed, to give a concrete analysis of the computational costs of the flexible feature extraction. Examples of synthetically warped and real multi-modal images are analyzed.

Science Data Processing↗

Agile Multi-Scale Decompositions for Automatic Image Registration

In recent works, the first and third authors developed an automatic image registration algorithm based on a multiscale hybrid image decomposition with anisotropic shearlets and isotropic wavelets. This prototype showed strong performance, improving robustness over registration with wavelets alone. However, this method imposed a strict hierarchy on the order in which shearlet and wavelet features were used in the registration process, and also involved an unintegrated mixture of MATLAB and C code. In this paper, we introduce a more agile model for generating features, in which a flexible and user-guided mix of shearlet and wavelet features are computed. Compared to the previous prototype, this method introduces a flexibility to the order in which shearlet and wavelet features are used in the registration process. Moreover, the present algorithm is now fully coded in C, making it more efficient and portable than the MATLAB and C prototype. We demonstrate the versatility and computational efficiency of this approach by performing registration experiments with the fully-integrated C algorithm. In particular, meaningful timing studies can now be performed, to give a concrete analysis of the computational costs of the flexible feature extraction. Examples of synthetically warped and real multi-modal images are analyzed.

Science Data Processing↗

Internship in Augmented and Virtual Reality - Rapid Model Import Tool

The integration of virtual and augmented reality, sometimes called mixed reality, is an emerging technology which will likely skyrocket overnight much in the way smartphones did a decade ago. Kennedy Space Center's Augmented and Virtual Reality (AVR) Lab is developing a Rapid Model Import Tool (RMIT) to create a quick and efficient way to bring NASA's complex engineering 3D models into virtual and augmented environments. The long-term objective is to create a tool that will ultimately benefit KSC engineers. Its various uses within NASA can potentially span from astronaut training, to marketing, to public outreach, to name a few. Unity is a prolific cross-platform game engine that allows users to build high quality 2D and 3D games for desktop, mobile, web, and game console platforms. It is perhaps also the most widely used software for virtual reality game development. At the AVR lab, we are looking at alternative uses of Unity to build tools for NASA engineers to perform design, development, testing, and training on spacecraft, rocket delivery systems, ground support equipment, and facilities at KSC. As an intern for the RMIT project, I am charged with the task of performing research on Unity-compatible file types to develop an efficient, affordable, preservative process to bring models from CATIA 3D engineering software into the Unity environment. With a tool called the NASA Enterprise Visualization Application (NEVA), developed by the Boeing Design Visualization group at KSC, we are able to easily convert CATIA's design models to. DAE (also known as COLLADA) and .OBJ file formats. I first reduce the polygon count of the model within CATIA itself, make any necessary tweaks to reduce the model further, and then export using NEVA. The .OBJ or. DAE files that I am left with are then converted by another intern to a Unity-compatible file format using a custom Python script. I have generated extensive documentation of this process in a NEVA User Guide. By the end of this semester, we will have built a solid framework for RMIT based on a thorough understanding of virtual reality specifications and file requirements, allowing future software development teams to go forward with development on the custom tool.

Leap Motion↗

Studying the 2019 Australian Bushfires Disaster using NASA Data: A Data-Driven Storytelling Approach

The 2019-2020 Australian fire season was particularly devastating, with millions of acres of land burned and impacts affecting Australian ecology, local populations and air quality, and the atmosphere. Australia saw unprecedented heat waves, with temperatures reaching 120 F (49.1 C) in January across central and eastern Australia. The fires gave rise to a host of atmospheric phenomenon, including smoke transport and lofting generated by storm-induced by fires, known as pyrocumulonimbus, reaching the stratosphere. NASA’s satellites not only tracked the event in real time, but also gathered data to further inform forecasting and response methods in the future. To better assist the public in understanding the lead up, impacts, and aftermath effects of these fires, the Science Outreach Team at NASA Langley Research Center’s Atmospheric Science Data Center (ASDC) Distributed Active Archive Center (DAAC) used Esri’s storymap tool to guide users through understanding relevant phenomenon, contributing factors, the effects this event has had on global atmospheric composition, and the science behind researching the tie between disasters and public health. The storymap uses data from the ASDC-supported NASA missions Measurements Of Pollution In The Troposphere (MOPITT), Cloud-Aerosol and Infrared Pathfinder Satellite Observation (CALIPSO), Clouds and the Earth’s Radiant Energy System (CERES), the Stratospheric Aerosol and Gas Experiment (SAGE III), and Multi-angle Imaging SpectroRadiometer (MISR). By using data-driven storytelling to communicate impacts of a large fire event, we hope to provide an accessible, engaging science outreach tool format.

Sanjana Paul↗

Preliminary SnowSAR Results from SnowEx 2017

SnowEx 2017 was the first in a multi-year series of airborne remote sensing campaigns, designed to address gaps in snow retrieval techniques in preparation for a future snow satellite mission. A variety of sensor types were flown to collect multi-sensor airborne data. In combination with detailed ground truth, this multi-sensor dataset enables critical trade studies to determine optimum sensor-plus-model combinations for different snow conditions and confounding factors. Up to half of terrestrial snow-covered areas are forested, and forests are a major confounding factor for global snow retrievals. Therefore, the main focus of SnowEx 2017 was evaluating the performance of the various sensing techniques to retrieve snow water equivalent (SWE) under steadily increasing amounts of forest cover. The primary site of Grand Mesa, Colorado, USA was selected for its natural gradients of forest density and SWE with a minimum of other factors. Radar retrievals of SWE relying on volume scattering have been studied for three decades, using a variety of frequencies, with varying degrees of success. The most recent volume scattering algorithms have focused on using 2 to 3 frequencies and both co- and cross-polarizations in the 9—18 GHz range (X through Ku bands). As such, one of the primary SnowEx 2017 airborne sensors was a dual-band (X & Ku) radar, the SnowSAR. Earlier versions of SnowSAR were used in 2011 and 2012 campaigns in Finland as well as a 2013 campaign in Canada. For SnowEx 2017, SnowSAR was installed on a P-3 aircraft from the US Naval Research Laboratory. Challenges associated with the aircraft, the installation, schedule, and flying weather all contrived to limit the amount of data collected. However, months of painstaking processing has yielded data that should be of value to the original objectives of SnowEx 2017. This paper will describe in detail the SnowSAR data that were collected, and provide quality assessments of the backscatter coefficient in terms of date, time, location, frequency, polarization, snow conditions, overlap with ground truth sites, forest density, etc. The challenges as well as potential remedies/caveats will be described in order to help guide users and maximize exploitation of this valuable data.

airborne sensors↗

An Updated Secondary Lunar Meteoroid Ejecta Model for Engineering Design

Introduction: The surface of the Moon is constantly being bombarded by a flux of meteoroids of various sizes. Impacts due to these meteoroids produce secondary ejecta material at much lower speeds but with a total mass larger than the original impactor. Details about the secondary ejecta are important for planning missions on the lunar surface. In this work, an updated ejecta model is presented called the Meteoroid Model of Secondary Ejecta (MeMoSeE), to re-place the Apollo-era ejecta model, NASA SP-8013 [1], in the SLS-SPEC 159 Design Specification for Natural Environments (DSNE) [2]. The model pro-duces secondary ejecta flux environments for a user-specified location on the lunar surface, and sorts the incoming secondary flux by angular direction and speed. Methods: MeMoSeE is separated into three parts: the inputs, the conversion step, and the integration of fluxes. Inputs to the model include the primary meteoroid fluxes and the primary near-Earth object (NEO) fluxes. Meteoroid fluxes, both asteroidal and cometary, are calculated using the Meteoroid Engineering Model (MEM3) [3] for different locations on the Moon. For each surface location, an ephemeris is generated using the JPL HORIZONS System [4] that feeds into MEM3. The NEO fluxes are approximated by the high-density population of MEM3 (i.e., only the directionality), where the speed distribution of the NEO fluxes is renormalized to match observations [5]. The regolith properties are used as defined in the DSNE [2]. The conversion step utilizes scaling laws given by Housen & Holsapple 2011 [6] to convert the primary impactor flux to the total mass of secondary ejecta. The ejecta distribution, at the point-of-impact (POI), is separated into a zenith angle and azimuthal angle distribution. The zenith angle distribution follows a beta distribution where the peak depends on the impact altitude angle and the impact azimuth [7]. We employ an ejecta azimuth distribution that is based on Rival & Mandeville 1999 [8] which focuses ejecta in the downstream direction for more oblique impacts. Finally, during the integration step, we sum secondary ejecta number fluxes at a particular region-of-interest (ROI) that originated from many POI locations over the entire surface of the Moon. We keep track of both altitude and azimuth angle bins as well as a range of speed bins, following the igloo gridding as done in MEM3 [9]. The ejecta particle size distribution and density is assumed to be the same as the lunar regolith [10, 2]. Results: The primary fluxes are computed for one Metonic cycle (19 years) for various locations over the lunar surface with a fixed orientation. Both the angular and speed distributions of the primary fluxes are dependent on the latitude and longitude. The over-all primary fluxes show a roughly 13% increase from the eastern limb to the western limb. In general, the speed distribution of the secondary fluxes span from a user-defined minimum speed to the escape speed of the Moon (2.38 km/s), roughly following a power-law relation [6]. Different parts of the speed distribution come from different primary impact locations on the Moon. The secondary ejecta is dominated by the slowest speeds, where these particles originate nearby the ROI. For speeds around 71% of the escape speed, the secondary ejecta originates from locations near the antipodal point. On the other hand, for secondary ejecta speeds that exceed roughly 90% the escape speed, the ejecta particles come from all over the lunar surface to the ROI. Comparing the secondary ejecta fluxes from MeMoSeE with NASA SP-8013 [1], there is a reduction by about 2-3 orders of magnitude for secondary ejecta particles greater than 1 µg. These estimates agree with recent findings from Bjorkman & Christiansen 2019 [11]. The secondary ejecta fluxes are also compared with the primary fluxes, where the ejecta fluxes are roughly an order of magnitude greater than the primary fluxes. References: [1] Cour-Palais, B. G., (1969) NASA SP-8013. [2] NASA SLS-SPEC-159 Rev. H (2020). [3] Moorhead, A. V., et al. (2019) JS&R, 1-17. [4] Giorgini, J. D., (2015) IAUGA, 29, 2256293. [5] Moorhead, A. V., (2020) Memo OSMA/MEO/Lunar-001. [6] Housen, K. R., and Holsapple, K. A., (2011) Icarus, 211(1), 856-875. [7] Gault, D. E., and Wedekind, J. A., (1978) L&PSCP, 9, 3843-3875. [8] Rival, M., and Mandeville, J., (1999) Space Debris, 1(1), 45-57. [9] Moorhead, A. V., (2019) MEM3 User Guide. [10] Carrier, W. D., (1973) The Moon, 6(3-4), 250-263. [11] Bjorkman, M. D. & Christiansen, E. L., (2019) ODC

impacts↗

Global Reference Atmospheric Model (GRAM) Advancements and Additions

Introduction:The Global Reference Atmospheric Model (GRAM) is one of the most widely used engineering models of the atmosphere. GRAM development and maintenance has been led by NASA Marshall Space Flight Center (MSFC). The NASA Science Mission Directorate (SMD) has provided funding support to upgrade the GRAMs since Fiscal Year 2018. NASA Langley Research Center has been working with MSFC on the upgrades.This presentation will provide details regarding the upgrades that have been made to the existing GRAMs, the development of new GRAMs, as well as the ongoing objectives, tasks, and milestones re-lated to the GRAM upgrades funded by NASA SMD. GRAM: The GRAMs are engineering-oriented atmospheric models that estimate mean values and statistical variations of the atmospheric properties for numerous planetary destinations.They provide mean values and variability for any point in the atmosphere as well as seasonal, geographic, and altitude variations. GRAM outputs include atmospheric density, temperature, pressure, winds, and chemical composition along a user-defined path.Theyhave been widely used by the engineering community because of their ability to create realistic dispersions. GRAMs have been integrated into high fidelity flight dynamic simulations of launch, entry, descent and landing (EDL), aerobraking and aerocapture. MSFC has been developing and updating GRAMs since 1974; GRAMs are currently available for Earth, Mars, Venus, Neptune, and Titan. GRAM Upgrade Status: Code Moderization.The planetary GRAMs are being rearchitected from Fortran to a common object-ori-entedC++ framework called the GRAM Suite. This new architecture creates a common GRAM library of data models and utilities. The first C++ releases of the existing planetary GRAMs (Mars, Venus, Neptune, and Titan-GRAM) in the GRAM Suite are straight conversions from the latest Fortran version. Model Upgrades.The focus of the model upgrade task is to improve the atmosphere models in the existing GRAMs and to establish a foundation for developing GRAMs for additional destinations. The GRAM ephemerishas been upgraded to the NASA Navigation and Ancillary Information Facility (NAIF) SPICE toolkit (version N0066). The calculation of the speed of sound has also been improved in the GRAMs. The GRAM team has received updated Mars General Circulation Model (MGCM) datasets from NASA Ames Research Center. Mars Global Ionosphere-Thermosphere Model (M-GITM) data is being obtained toreplace the Mars Thermospheric General Circulation Model (MTGCM) data in legacy Mars-GRAM. M-GITM and updated MGCM data will be incorporated into a future GRAM Suite release.Twoprojects that will improve the atmospheric model data in the GRAMs have been funded by the GRAM team since Fiscal Year 2020. Sanjay Limaye and Patrick Fry at the University of Wisconsin are reanalyzing the Venus Express radio occultation observations and analyzing the Akatsukiradio occultation observations.This will lead tothe calculation of number density, temperature, and pressure profiles for the 40-90 km altitude range. Kunio Sayanagi, Justin Garland, and Ryan McCabeat Hampton University are developing empirical global models for Venus,Jupiter, Saturn, Uranus, Neptune, and Titan that incorporates the latest data available for each of these planetary destinations. Upgraded GRAM Releases. GRAM Suite Version 1.0 was released in May 2020 and contains the rearchitected Neptune-GRAM, including the common GRAM framework and planet–specific code. GRAM Suite Version 1.1 was released in September 2020 and addedthe rearchitected Titan-GRAM to the GRAM Suite. A User Guide and Programmer’s Manualarereleased with all GRAMs. The rearchitected Mars and Venus-GRAMs will be released in upcomingversions of the GRAM Suite. New GRAM Releases. New GRAMs have been de-veloped for Uranus and Jupiter. Uranus-GRAM is based on an individual profile generated by Gary Allen (ARC) from Voyager 2 occultation data and will be released in GRAM Suite Version 1.2. Jupiter-GRAM is based on individual profile produced from Al Seiff’s Ju-piter model[1].Jupiter-GRAM will be released in GRAM Suite Version 1.3. Saturn-GRAM is currently under development and will be released in a future version of the GRAM Suite. Conclusions: GRAMs are vital and frequently used toolsets. Releases of the GRAM Suite, upgrades of the existing planetary GRAMs, and development of new planetary GRAMs are ongoing. NASA SMD funding has been essential to addressing current limitations and accomplishing GRAM developmental goals. Continua-tion ofSMD fundingwill ensure the development, up-grades, and maintenance of the GRAMs. References: [1] Seiff, A., et al. (1998) JGR, 103, 22,857-22,889. Acknowledgments: The authors gratefully acknowledge support from the NASA SMD

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