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NASA NTRS2006

Precipitation and Latent Heating Distributions from Satellite Passive Microwave Radiometry: Improved Method and Uncertainties - Part 1

A revised Bayesian algorithm for estimating surface rain rate, convective rain proportion, and latent heating profiles from satellite-borne passive microwave radiometer observations over ocean backgrounds is described. The algorithm searches a large database of cloud-radiative model simulations to find cloud profiles that are radiatively consistent with a given set of microwave radiance measurements. The properties of these radiatively consistent profiles are then composited to obtain best estimates of the observed properties. The revised algorithm is supported by an expanded and more physically consistent database of cloud-radiative model simulations. The algorithm also features a better quantification of the convective and nonconvective contributions to total rainfall, a new geographic database, and an improved representation of background radiances in rain-free regions. Bias and random error estimates are derived from applications of the algorithm to synthetic radiance data, based upon a subset of cloud-resolving model simulations, and from the Bayesian formulation itself. Synthetic rain-rate and latent heating estimates exhibit a trend of high (low) bias for low (high) retrieved values. The Bayesian estimates of random error are propagated to represent errors at coarser time and space resolutions, based upon applications of the algorithm to TRMM Microwave Imager (TMI) data. Errors in TMI instantaneous rain-rate estimates at 0.5 -resolution range from approximately 50% at 1 mm/h to 20% at 14 mm/h. Errors in collocated spaceborne radar rain-rate estimates are roughly 50%-80% of the TMI errors at this resolution. The estimated algorithm random error in TMI rain rates at monthly, 2.5deg resolution is relatively small (less than 6% at 5 mm day.1) in comparison with the random error resulting from infrequent satellite temporal sampling (8%-35% at the same rain rate). Percentage errors resulting from sampling decrease with increasing rain rate, and sampling errors in latent heating rates follow the same trend. Averaging over 3 months reduces sampling errors in rain rates to 6%-15% at 5 mm day.1, with proportionate reductions in latent heating sampling errors.

Olson, William S.↗
NASA NTRS2003

Aging Wire Insulation Assessment by Phase Spectrum Examination of Ultrasonic Guided Waves

Wire integrity has become an area of concern to the aerospace community including DoD, NASA, FAA, and Industry. Over time and changing environmental conditions, wire insulation can become brittle and crack. The cracks expose the wire conductor and can be a source of equipment failure, short circuits, smoke, and fire. The technique of using the ultrasonic phase spectrum to extract material properties of the insulation is being examined. Ultrasonic guided waves will propagate in both the wire conductor and insulation. Assuming the condition of the conductor remains constant then the stiffness of the insulator can be determined by measuring the ultrasonic guided wave velocity. In the phase spectrum method the guided wave velocity is obtained by transforming the time base waveform to the frequency domain and taking the phase difference between two waveforms. The result can then be correlated with a database, derived by numerical model calculations, to extract material properties of the wire insulator. Initial laboratory tests were performed on a simple model consisting of a solid cylinder and then a solid cylinder with a polymer coating. For each sample the flexural mode waveform was identified. That waveform was then transformed to the frequency domain and a phase spectrum was calculated from a pair of waveforms. Experimental results on the simple model compared well to numerical calculations. Further tests were conducted on aircraft or mil-spec wire samples, to see if changes in wire insulation stiffness can be extracted using the phase spectrum technique.

Anastasi, Robert F.↗
NASA NTRS1988

Studying Turbulence Using Numerical Simulation Databases, 2. Proceedings of the 1988 Summer Program

The focus of the program was on the use of direct numerical simulations of turbulent flow for study of turbulence physics and modeling. A special interest was placed on turbulent mixing layers. The required data for these investigations were generated from four newly developed codes for simulation of time and spatially developing incompressible and compressible mixing layers. Also of interest were the structure of wall bounded turbulent and transitional flows, evaluation of diagnostic techniques for detection of organized motions, energy transfer in isotropic turbulence, optical propagation through turbulent media, and detailed analysis of the interaction of vortical structures.

Source record↗
NASA NTRSDate not supplied

Quantifying the Sensitivity of Condition Incidence Parameters in the Evidence Library

One approach to quantifying spaceflight risk at NASA makes use event driven probabilistic techniques. The Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT) is such a tool that estimates medical risk metrics via simulation and enables optimization of medical resources subject to mission constraints [1]. Previous analyses have informed medical set composition, exercise countermeasures, and water intake, where each analysis quantifies the risk associated with proposed variations in system design. As future mission profiles extend beyond Low-Earth Orbit (LEO) and lengthen in duration, understanding these risks and contributing factors is critical. MEDPRAT employs Monte Carlo sampling techniques to simulate missions and track the occurrence of medical events. These events follow fault-tree-like progressions through levels of severity and mitigation via medical treatment to many possible outcomes and these are reported throughout the mission. Making this possible, are the medical databases that contain evidence gathered by the Human Research Program (HRP). Quantifying the impact of uncertainty or variability in the input data is an important step in evaluating the credibility of modeling and simulation results. In this work, we investigate the sensitivity of medical risk metrics with respect to the condition incidence parameters within the Evidence Library (EL) [2] as the medical database input for MEDPRAT. The medical conditions, contained in the EL, are equipped with incidence rates that describe the likelihood that the condition will occur. These incidence rates reflect historical spaceflight data or when appropriate, terrestrial data. In this presentation, we will explore how uncertainty in these rates propagate to the medical risk described by MEDPRAT. These results identify the conditions and parameters with the largest contribution to medical risks.

Ian Lim↗
NASA NTRS2003

Evaluation of Production Cross Sections of Li, Be, B in CR

Accurate evaluation of the production cross section of light elements is important for models of cosmic ray (CR) propagation, galactic chemical evolution, and cosmological studies. However, the experimental spallation cross section data are scarce and often unavailable to CR community while semi-empirical systematics are frequently wrong by a significant factor. Running sophisticated nuclear codes is not an option of choice for everyone either. We use the Los Alamos versions of the Quark-Gluon String Model code LAQGSM and the improved Cascade-Exciton Model code CEM2k together with all available data from Los Alamos Nuclear Laboratory (LANL) nuclear database to produce evaluated production cross sections of isotopes of Li, Be, and B suitable for astrophysical applications. The LAQGSM and CEM2k models have been shown to reproduce well nuclear reactions and hadronic data in the range 0.01-800 GeV/nucleon.

Moskalenko, I. V.↗
NASA NTRS1994

Survey of Volumetric Grid Generators

This document is the result of an Internet Survey of Volumetric grid generators. As such we have included information from only the responses which were sent to us. After the initial publication and posting of this survey, we would encourage authors and users of grid generators to send further information. Here is the initial query posted to SIGGRID@nas and the USENET group sci.physics.computational.fluid-dynamics. Date: Sun, 30 Jan 94 11:37:52 -0800 From: woo (Alex Woo x6010 227-6 rm 315) Subject: Info Sought for Survey of Grid Generators I am collecting information and reviews of both government sponsored and commercial mesh generators for large scientific calculations, both block structured and unstructured. If you send me a review of a mesh generator, please indicate its availability and cost. If you are a commercial concern with information on a product, please also include references for possible reviewers. Please email to woo@ra-next.arc.nasa.gov. I will post a summary and probably write a short note for the IEEE Antennas and Propagation Magazine. Alex Woo, MS 227-6 woo@ames.arc.nasa.gov NASA Ames Research Center NASAMAIL ACWOO Moffett Field, CA 94035-1000 SPANET 24582::W00 (415) 604-6010 (FAX) 604-4357 fhplabs,decwrl,uunet)!ames!woo Disclaimer: These are not official statements of NASA or EMCC. We did not include all the submitted text here. Instead we have created a database entry in the freely available and widely used BIBTeX format which has an Uniform Resource Locator (URL) field pointing to more details. The BIBTeX database is modeled after those available from the BIBNET project at University of Utah.

Woo, Alex↗
NASA NTRS2007

Improvements to NASA's Debris Assessment Software

NASA's Debris Assessment Software (DAS) has been substantially revised and expanded. DAS is designed to assist NASA programs in performing orbital debris assessments, as described in NASA s Guidelines and Assessment Procedures for Limiting Orbital Debris. The extensive upgrade of DAS was undertaken to reflect changes in the debris mitigation guidelines, to incorporate recommendations from DAS users, and to take advantage of recent software capabilities for greater user utility. DAS 2.0 includes an updated environment model and enhanced orbital propagators and reentry-survivability models. The ORDEM96 debris environment model has been replaced by ORDEM2000 in DAS 2.0, which is also designed to accept anticipated revisions to the environment definition. Numerous upgrades have also been applied to the assessment of human casualty potential due to reentering debris. Routines derived from the Object Reentry Survival Analysis Tool, Version 6 (ORSAT 6), determine which objects are assessed to survive reentry, and the resulting risk of human casualty is calculated directly based upon the orbital inclination and a future world population database. When evaluating reentry risks, the user may enter up to 200 unique hardware components for each launched object, in up to four nested levels. This last feature allows the software to more accurately model components that are exposed below the initial breakup altitude. The new DAS 2.0 provides an updated set of tools for users to assess their mission s compliance with the NASA Safety Standard and does so with a clear and easy-to-understand interface. The new native Microsoft Windows graphical user interface (GUI) is a vast improvement over the previous DOS-based interface. In the new version, functions are more-clearly laid out, and the GUI includes the standard Windows-style Help functions. The underlying routines within the DAS code are also improved.

Opiela, J.↗
NASA NTRS2017

Isolating Added Mass Load Components of CPAS Main Clusters

The current simulation for the Capsule Parachute Assembly System (CPAS) lacks fidelity in representing added mass for the 116 ft Do ringsail Main parachute. The availability of 3-D models of inflating Main canopies allowed for better estimation the enclosed air volume as a function of time. This was combined with trajectory state information to estimate the components making up measured axial loads. A proof-of-concept for an alternate simulation algorithm was developed based on enclosed volume as the primary independent variable rather than drag area growth. Databases of volume growth and parachute drag area vs. volume were developed for several flight tests. Other state information was read directly from test data, rather than numerically propagated. The resulting simulated peak loads were close in timing and magnitude to the measured loads data. However, results are very sensitive to data curve fitting and may not be suitable for Monte Carlo simulations. It was assumed that apparent mass was either negligible or a small fraction of enclosed mass, with little difference in results.

Ray, Eric S.↗
NASA NTRS2001

The Transfer Function Model as a Tool to Study and Describe Space Weather Phenomena

The Transfer Function Model (TFM) is a semi-analytical, linear model that is designed especially to describe thermospheric perturbations associated with magnetic storms and substorm. activity. It is a multi-constituent model (N2, O, He H, Ar) that accounts for wind induced diffusion, which significantly affects not only the composition and mass density but also the temperature and wind fields. Because the TFM adopts a semianalytic approach in which the geometry and temporal dependencies of the driving sources are removed through the use of height-integrated Green's functions, it provides physical insight into the essential properties of processes being considered, which are uncluttered by the accidental complexities that arise from particular source geometrie and time dependences. Extending from the ground to 700 km, the TFM eliminates spurious effects due to arbitrarily chosen boundary conditions. A database of transfer functions, computed only once, can be used to synthesize a wide range of spatial and temporal sources dependencies. The response synthesis can be performed quickly in real-time using only limited computing capabilities. These features make the TFM unique among global dynamical models. Given these desirable properties, a version of the TFM has been developed for personal computers (PC) using advanced platform-independent 3D visualization capabilities. We demonstrate the model capabilities with simulations for different auroral sources, including the response of ducted gravity waves modes that propagate around the globe. The thermospheric response is found to depend strongly on the spatial and temporal frequency spectra of the storm. Such varied behavior is difficult to describe in statistical empirical models. To improve the capability of space weather prediction, the TFM thus could be grafted naturally onto existing statistical models using data assimilation.

Porter, Hayden S.↗
NASA NTRS2008

The NASA MSFC Earth Global Reference Atmospheric Model-2007 Version

Reference or standard atmospheric models have long been used for design and mission planning of various aerospace systems. The NASA/Marshall Space Flight Center (MSFC) Global Reference Atmospheric Model (GRAM) was developed in response to the need for a design reference atmosphere that provides complete global geographical variability, and complete altitude coverage (surface to orbital altitudes) as well as complete seasonal and monthly variability of the thermodynamic variables and wind components. A unique feature of GRAM is that, addition to providing the geographical, height, and monthly variation of the mean atmospheric state, it includes the ability to simulate spatial and temporal perturbations in these atmospheric parameters (e.g. fluctuations due to turbulence and other atmospheric perturbation phenomena). A summary comparing GRAM features to characteristics and features of other reference or standard atmospheric models, can be found Guide to Reference and Standard Atmosphere Models. The original GRAM has undergone a series of improvements over the years with recent additions and changes. The software program is called Earth-GRAM2007 to distinguish it from similar programs for other bodies (e.g. Mars, Venus, Neptune, and Titan). However, in order to make this Technical Memorandum (TM) more readable, the software will be referred to simply as GRAM07 or GRAM unless additional clarity is needed. Section 1 provides an overview of the basic features of GRAM07 including the newly added features. Section 2 provides a more detailed description of GRAM07 and how the model output generated. Section 3 presents sample results. Appendices A and B describe the Global Upper Air Climatic Atlas (GUACA) data and the Global Gridded Air Statistics (GGUAS) database. Appendix C provides instructions for compiling and running GRAM07. Appendix D gives a description of the required NAMELIST format input. Appendix E gives sample output. Appendix F provides a list of available parameters to enable the user to generate special output. Appendix G gives an example and guidance on incorporating GRAM07 as a subroutine in other programs such as trajectory codes or orbital propagation routines.

Leslie, F.W.↗
NASA NTRSDate not supplied

Enabling Supersonic Over-Land Flight Using Computational Modeling

NASA's QueSST mission is interested in exploring the potential of commercial, over-land supersonic flight, which has been banned since 1973 due to the noise intensity of the sonic booms that supersonic vehicles create. NASA has partnered with Lockheed Martin to design and construct an experimental aircraft, the X-59, that will shape the sonic boom to achieve a perceived loudness on the ground that is lower than 75dB. In this talk, we present new developments in the Launch Ascent and Vehicle Aerodynamics (LAVA) CFD solver framework which are tailored to the analysis of supersonic vehicles, like the X-59, and sonic boom propagation. Utilizing a high-order space marching method, adjoint-based grid adaptation, and robust database capabilities have enabled significant cost savings over traditional CFD methods for the same level of accuracy in perceived boom loudness. Example cases demonstrating the toolset are presented, along with comparisons to experimental wind tunnel data. These developments will enable LAVA to quickly and accurately provide simulation data to the project during X-59's first and subsequent flights in 2024 and beyond.

CST↗
NASA NTRS2003

Measurement of Charged Particle Interactions in Spacecraft and Planetary Habitat Shielding Materials

Accurate models of health risks to astronauts on long-duration missions outside the geomagnetosphere will require a full understanding of the radiation environment inside a spacecraft or planetary habitat. This in turn requires detailed knowledge of the flux of incident particles and their propagation through matter, including the nuclear interactions of heavy ions that are a part of the Galactic Cosmic Radiation (GCR). The most important ions are likely to be iron, silicon, oxygen, and carbon. Transport of heavy ions through complex shielding materials including self-shielding of tissue modifies the radiation field at points of interest (e.g., at the blood-forming organs). The incident flux is changed by two types of interactions: (1) ionization energy loss, which results in reduced particle velocity and higher LET (Linear Energy Transfer); and (2) nuclear interactions that fragment the incident nuclei into less massive ions. Ionization energy loss is well understood, nuclear interactions less so. Thus studies of nuclear fragmentation at GCR-like energies are needed to fill the large gaps that currently exist in the database. These can be done at only a few accelerator facilities where appropriate beams are available. Here we report results from experiments performed at the Brookhaven National Laboratory s Alternating Gradient Synchrotron (AGS) and the Heavy Ion Medical Accelerator in Chiba, Japan (HIMAC). Recent efforts have focused on extracting charge-changing and fragment production cross sections from silicon beams at 400, 600, and 1200 MeV/nucleon. Some energy dependence is observed in the fragment production cross sections, and as in other data sets the production of fragments with even charge numbers is enhanced relative to those with odd charge numbers. These data are compared to the NASA-LaRC model NUCFRG2. The charge-changing cross section data are compared to recent calculations using an improved model due to Tripathi, which accurately predicts the observed (slight) energy dependence. An additional set of data will be presented from an analysis of shielding material performance in the 1 GeV/nucleon iron beam at the AGS. A wide variety of candidate materials for spacecraft construction, as well as elemental targets, have been placed in this beam and their effects on transmitted dose and dose equivalent measured. The results support a prediction by J. Wilson et al. that hydrogen-loaded materials give the greatest dose reduction per unit mass.

Zeitlin, Cary J.↗
NASA NTRS2017

Development of a Numerical Model of Hypervelocity Impact into a Pressurized Composite Overwrapped Pressure Vessel

As the outlook for space exploration becomes more ambitious and spacecraft travel deeper into space than ever before, it is increasingly important that propulsion systems perform reliably within the space environment. The increased reliability compels designers to increase design margin at the expense of system mass, which contrasts with the need to limit vehicle mass to maximize payload. Such are the factors that motivate the integration of high specific strength composite materials in the construction of pressure vessels commonly referred to as composite overwrapped pressure vessels (COPV). The COPV consists of a metallic liner for the inner shell of the COPV that is stiff, negates fluid permeation and serves as the anchor for composite laminates or filaments, but the liner itself cannot contain the stresses from the pressurant it contains. The compo-site-fiber reinforced polymer (CFRP) is wound around the liner using a combination of hoop (circumferential) and helical orientations. Careful consideration of wrap orientation allows the composite to evenly bear structural loading and creates the COPV's characteristic high strength to weight ratio. As the CFRP overwrap carries most of the stresses induced by pressurization, damage to the overwrap can affect mission duration, mission success and potentially cause loss-of-vehicle/loss-of-crew. For this reason, it is critical to establish a fundamental understanding of the mechanisms involved in the failure of a stressed composite such as that of the COPV. One of the greatest external threats to the integrity of a spacecraft's COPV is an impact from the meteoroid and orbital debris environments (MMOD). These impacts, even from submillimeter particles, generate extremely high stress states in the CFRP that can damage numerous fibers. As a result of this possibility, initial assumptions in survivability analysis for some human-rated NASA space-craft have assumed that any alteration of the vessel due to impact is considered a catastrophic failure. This assumption is conservative and made due to lack of knowledge on the level of allow-able damage to the composite overwrap that can be sustained and still allow successful completion of the mission. To quantify the allowable damage level to the composite overwrap involves assessing stress redistribution following damage as well as evaluating possible time-dependent mechanisms involved in the COPV response to an impact event. Limited published work in this subject has shown that COPV can withstand at least some level of damage due to high energy impacts. These observations have been confirmed and expanded upon in recent experimental research performed by NASA. This research has demonstrated that there is not only robustness in a COPV to compensate for CFRP damage, but has also identified two significant failure modes for pressurized COPV. The lowest threshold failure mode involves the perforation of the vessel, and the highest threshold failure mode is the catastrophic rupture. While both of these failure modes mean a loss of the COPV, system robustness affords some tolerance to the venting as opposed to the more catastrophic rupture. As a consequence, it is necessary to understand the conditions that result in the transition between these failure modes. The aforementioned experimental research has been performed in both the unpressurized and pressurized condition to identify the damage level that triggered the failure thresh-old. This COPV test program was sponsored by the NASA Engineering and Safety Center (NESC), and tests were performed at NASA White Sands Test Facility (WSTF). Planning and coordination were provided by NASA JSC Hypervelocity Impact Technology (HVIT) group, and the COPVs were provided by the ISS Program. Unpressurized testing has been conducted at the pressure of the vacuum test chamber, while, the pressurized testing has been conducted at 290 +/- 10 bar (4,200  100 psi) using nitrogen as the pressurizing gas, which corresponds to the design pressure for the target COPV. In this research, spherical aluminum projectiles with varying diameter has been chosen as the impactor. For the unpressurized COPV, the dependence of penetration up to the dependence of hole size in the liner has been obtained as a function of impact conditions. For the pressurized research, the dependence of penetration up to rupture has been obtained as a function of im-pact conditions. Two representative post-test photographs of the failed COPV's from a nor-mal impact into the COPV surface are shown in Fig. 1. These images display the dramatic difference between failure modes, venting (Fig. 1a) and rupture (Fig. 1b). For venting, liner perforation, severed composite fibers/tows and ply delamination are commonly observed damage characteristics of this COPV failure mode. In the case of rupture, the COPV typically experienced a separation of its domed regions and severe break-up of the cylindrical region. Fully understanding the transition from venting to rupture experimentally is costly and potentially unachievable for conditions that cannot be generated in the laboratory. These shortcomings have motivated the performance of three-dimensional numerical simulations to expand the existing experimental database. These simulations have been carried out with the nonlinear-structural-dynamics, analysis-tool, CTH. A typical pressure contour plot from an impact simulation of an entire COPV is shown in Fig. 2. To generate the COPV stress state without initiating a shock wave, the pressure in the simulated COPV is ramped up to the final pressure over a millisecond prior to impact of the projectile with nitrogen gas. Figure 2a shows the system in this initial condition. After one millisecond, a projectile is initiated into the simulation and impacts the COPV. Figure 2b shows the system after this impact. In the figure, the onset of venting is represented as the change in pressure (μbar), red to green, at the perforation site. Also seen in the figure is the eroded projectile that had passed into the COPV vessel with the generated shock wave in the pressurant propagating just ahead of the material. In this paper, pertinent experimental details and the development of the material constitutive models necessary for this work along with the efforts to validate their use are dis-cussed. The simulation results are presented and compared with the NASA experimental observations. While work is on-going from this effort, early observations pertinent to the failure threshold are presented.

Garcia, M. A.↗
NASA NTRS2011

Vehicle Integrated Prognostic Reasoner (VIPR) 2010 Annual Final Report

Honeywell's Central Maintenance Computer Function (CMCF) and Aircraft Condition Monitoring Function (ACMF) represent the state-of-the art in integrated vehicle health management (IVHM). Underlying these technologies is a fault propagation modeling system that provides nose-to-tail coverage and root cause diagnostics. The Vehicle Integrated Prognostic Reasoner (VIPR) extends this technology to interpret evidence generated by advanced diagnostic and prognostic monitors provided by component suppliers to detect, isolate, and predict adverse events that affect flight safety. This report describes year one work that included defining the architecture and communication protocols and establishing the user requirements for such a system. Based on these and a set of ConOps scenarios, we designed and implemented a demonstration of communication pathways and associated three-tiered health management architecture. A series of scripted scenarios showed how VIPR would detect adverse events before they escalate as safety incidents through a combination of advanced reasoning and additional aircraft data collected from an aircraft condition monitoring system. Demonstrating VIPR capability for cases recorded in the ASIAS database and cross linking them with historical aircraft data is planned for year two.

Hadden, George D.↗
NASA NTRS2005

Forecasting of Storm Surge Floods Using ADCIRC and Optimized DEMs

Increasing the accuracy of storm surge flood forecasts is essential for improving preparedness for hurricanes and other severe storms and, in particular, for optimizing evacuation scenarios. An interactive database, developed by WorldWinds, Inc., contains atlases of storm surge flood levels for the Louisiana/Mississippi gulf coast region. These atlases were developed to improve forecasting of flooding along the coastline and estuaries and in adjacent inland areas. Storm surge heights depend on a complex interaction of several factors, including: storm size, central minimum pressure, forward speed of motion, bottom topography near the point of landfall, astronomical tides, and most importantly, maximum wind speed. The information in the atlases was generated in over 100 computational simulations, partly by use of a parallel-processing version of the ADvanced CIRCulation (ADCIRC) model. ADCIRC is a nonlinear computational model of hydrodynamics, developed by the U.S. Army Corps of Engineers and the US Navy, as a family of two- and three-dimensional finite element based codes. It affords a capability for simulating tidal circulation and storm surge propagation over very large computational domains, while simultaneously providing high-resolution output in areas of complex shoreline and bathymetry. The ADCIRC finite-element grid for this project covered the Gulf of Mexico and contiguous basins, extending into the deep Atlantic Ocean with progressively higher resolution approaching the study area. The advantage of using ADCIRC over other storm surge models, such as SLOSH, is that input conditions can include all or part of wind stress, tides, wave stress, and river discharge, which serve to make the model output more accurate.

Valenti, Elizabeth↗
NASA NTRSDate not supplied

Flux Comparison of Master-8 and Ordem 3.1 Modelled Space Debris Population

With ESA’s Meteoroid And Space debris Terrestrial Environment Reference (MASTER-8) model and NASA’s Orbital Debris Engineering Model(ORDEM) 3.1, the two premier orbital debris engineering models have been officially released. The two models come with significant enhancements and now represent state-of-the-art orbital debris modelling for their respective agencies. Both models provide the community with estimates of the space debris environment from low Earth orbit (LEO) up to at least geostationary altitude. The MASTER population is an event-based simulation of all known events that generate debris and objects that are part of the U.S. Space Surveillance Network (SSN) catalog, which provides coverage of objects with diameters down to approximately 10cm in LEO and 1 m in geosynchronous Earth orbit (GEO). Different models are used to simulate the artificial objects and their orbit evolution over time. These models are called “sources” since they assign an origin to each individual object and consist of fragments, solid rocket motor (SRM) remainders, sodium-potassium(NaK) droplets, paintflakes, ejecta, and multi-layer insulation (MLI) fragments. The objects from each source are characterized by having individual release mechanisms, as well as orbital distributions, material composition, size, and mass distributions. Dedicated radar and telescope observation data is used to calibrate the model for objects larger than 1 cm in LEO and larger than 10 cm in GEO. For calibrating the small-sized objects, below 1 cm, impact data from returned surfaces are analyzed. Because the >1cm object population is dominated by fragments, the fragmentation event database was updated to include new events, as well as re-evaluate past events. Special attention was drawn to re-evaluating theFengyun-1C anti-satellite test from 2007 and Cosmos-Iridium collision event from 2009 since these events shape the fragment population because of their severity. After 2009, the two largest fragmentations in terms of number of tracked debris are the Briz-M explosion in 2012 and the NOAA-16explosion in 2015. In total, there are 261 confirmed fragmentations in the database up to November 2016.The baseline population for ORDEM 3.1 is based on the U.S. SSN catalog, and observational datasets from radar, in situ, and optical sources provide a foundation from which the model populations are statistically extrapolated to smaller size regions. These regions are not well-covered by the SSN catalog yet may pose the greatest threat to operational spacecraft. The NASA Standard Satellite Breakup Model is used to generate fragments greater than 1mm from collisions and explosions, and these fragment populations are scaled using ground-based radar data. Specific major debris-producing events, including the Fengyun-1C, Iridium 33, and Cosmos2251 debris clouds, and unique populations, such as NaK droplets, were re-examined, modelled, and added to the ORDEM environment separately. Optical measurement data is used to model the GEO population down to 10 cm. The debris environment is propagated using NASA’s LEO-to-GEO Environment Debris model, and future explosions of intact objects and collisions involving objects greater than 10 cm are assessed statistically. The environment from a few millimetres down to 10 𝜇m is modelled using a special degradation model where small particles are generated from intact spacecraft and rocket bodies, then the populations are scaled to fit in situ cratering data from Space Shuttle returned surfaces. Fragments smaller than 10 cm are differentiated based on material density categories, i.e., high-, medium-, and low-density, to better characterize the potential debris risk posed to upper stages and spacecraft. This paper will discuss the MASTER and ORDEM approaches for modelling populations and compare fluxes for specific orbits, including sun-synchronous, ISS-altitude, geosynchronous transfer, and GEO. In the end, a conclusion is drawn towards the importance of having multiple fundamentally different, yet validated, models to estimate the space debris population.

Andre Horstmann↗
NASA NTRS2006

Forecasting of Storm-Surge Floods Using ADCIRC and Optimized DEMs

Increasing the accuracy of storm-surge flood forecasts is essential for improving preparedness for hurricanes and other severe storms and, in particular, for optimizing evacuation scenarios. An interactive database, developed by WorldWinds, Inc., contains atlases of storm-surge flood levels for the Louisiana/Mississippi gulf coast region. These atlases were developed to improve forecasting of flooding along the coastline and estuaries and in adjacent inland areas. Storm-surge heights depend on a complex interaction of several factors, including: storm size, central minimum pressure, forward speed of motion, bottom topography near the point of landfall, astronomical tides, and, most importantly, maximum wind speed. The information in the atlases was generated in over 100 computational simulations, partly by use of a parallel-processing version of the ADvanced CIRCulation (ADCIRC) model. ADCIRC is a nonlinear computational model of hydrodynamics, developed by the U.S. Army Corps of Engineers and the US Navy, as a family of two- and three-dimensional finite-element-based codes. It affords a capability for simulating tidal circulation and storm-surge propagation over very large computational domains, while simultaneously providing high-resolution output in areas of complex shoreline and bathymetry. The ADCIRC finite-element grid for this project covered the Gulf of Mexico and contiguous basins, extending into the deep Atlantic Ocean with progressively higher resolution approaching the study area. The advantage of using ADCIRC over other storm-surge models, such as SLOSH, is that input conditions can include all or part of wind stress, tides, wave stress, and river discharge, which serve to make the model output more accurate. To keep the computational load manageable, this work was conducted using only the wind stress, calculated by using historical data from Hurricane Camille, as the input condition for the model. Hurricane storm-surge simulations were performed on an eight-node Linux computer cluster. Each node contained dual 2-GHz processors, 2GB of memory, and a 40GB hard drive. The digital elevation model (DEM) for this region was specified using a combination of Navy data (over water), NOAA data (for the coastline), and optimized Interferometric Synthetic Aperture Radar data (over land). This high-resolution topographical data of the Mississippi coastal region provided the ADCIRC model with improved input with which to calculate improved storm-surge forecasts.

Valenti, Elizabeth↗
NASA NTRS1994

Automatic cataloguing and characterization of Earth science data using SE-trees

In the future, NASA's Earth Observing System (EOS) platforms will produce enormous amounts of remote sensing image data that will be stored in the EOS Data Information System. For the past several years, the Intelligent Data Management group at Goddard's Information Science and Technology Office has been researching techniques for automatically cataloguing and characterizing image data (ADCC) from EOS into a distributed database. At the core of the approach, scientists will be able to retrieve data based upon the contents of the imagery. The ability to automatically classify imagery is key to the success of contents-based search. We report results from experiments applying a novel machine learning framework, based on Set-Enumeration (SE) trees, to the ADCC domain. We experiment with two images: one taken from the Blackhills region in South Dakota; and the other from the Washington DC area. In a classical machine learning experimentation approach, an image's pixels are randomly partitioned into training (i.e. including ground truth or survey data) and testing sets. The prediction model is built using the pixels in the training set, and its performance is estimated using the testing set. With the first Blackhills image, we perform various experiments achieving an accuracy level of 83.2 percent, compared to 72.7 percent using a Back Propagation Neural Network (BPNN) and 65.3 percent using a Gaussain Maximum Likelihood Classifier (GMLC). However, with the Washington DC image, we were only able to achieve 71.4 percent, compared with 67.7 percent reported for the BPNN model and 62.3 percent for the GMLC.

Rymon, Ron↗