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Supporting Weather Data

Since its founding in 1992, Global Science & Technology, Inc. (GST), of Greenbelt, Maryland, has been developing technologies and providing services in support of NASA scientific research. GST specialties include scientific analysis, science data and information systems, data visualization, communications, networking and Web technologies, computer science, and software system engineering. As a longtime contractor to Goddard Space Flight Center s Earth Science Directorate, GST scientific, engineering, and information technology staff have extensive qualifications with the synthesis of satellite, in situ, and Earth science data for weather- and climate-related projects. GST s experience in this arena is end-to-end, from building satellite ground receiving systems and science data systems, to product generation and research and analysis.

Source record↗

In-Situ XRD/XRF to Support Life Detection on Mars

X-ray diffraction / X-ray fluorescence (XRD/XRF) analysis provides the most comprehensive mineralogical / compositional characterization of rocks and soils of any flight-capable technique. XRD data provide quantitative mineralogy (including abundance of X-ray amorphous materials) and crystal chemistry (structure, elemental composition and valence state), and XRF data provide complimentary major, minor, and some trace element abundances. Both types of data are important in evaluating habitability (environment of formation) and biosignature preservation/degradation (post-depositional diagenetic change). Whether or not a relict biosignature is detected, the mineral assemblage and its geochemistry can be used to determine the habitability of an ancient environment (e.g., salinity, pH, temperature), and to identify potential sources of energy for life (e.g., elements in different redox states). In this respect, a null result (a habitable environment lacking evidence of life) can play an important role in constraining the parameters of the search. Conversely, diagenetic alteration (taphonomic change) resulting from post-depositional variations in temperature, pressure or fluid chemistry can preserve evidence of biogenicity, erase such evidence completely or indeed can provide for post-depositional habitable conditions in the subsurface. XRD / XRF data are critical to these determinations. The CheMin instrument on the Mars Science Laboratory (MSL) Curiosity rover is the first XRD instrument flown in space. CheMin operates in transmission geometry with a Co X-ray source to minimize fluorescence from iron. Diffracted photons are collected with an energy-sensitive charge-coupled device (CCD). The position of the diffracted photons provides structural information for minerals, whereas the energy of sample-generated X-ray fluorescence photons provides elemental information, though these XRF data are qualitative. Mineralogical data from the CheMin XRD identified the three circumstances above: habitable depositional environments (e.g., Yellowknife Bay), habitable subsurface/diagenetic environments (e.g., throughout the Murray formation), and diagenetic conditions that may destroy evidence of habitability (e.g., oxidative and acidic environments at Vera Rubin ridge). Technological advances in X-ray technology and lessons learned from the operation of CheMin on Mars have resulted in a next-generation XRD/XRF, called CheMinX. Replacement of CheMin’s CCD with an array of hybrid pixel detectors and improvements in focusing optics dramatically decrease analysis time (15 minutes vs. 22 hours for MSL-CheMin) and result in a better angular resolution (0.18 vs. 0.30 °2θ for MSL-CheMin). This increased resolution improves mineral detection, including discrimination between types of pyroxenes, which is not possible with MSL-CheMin data. The hybrid pixel detectors do not require cooling like the MSL-CheMin CCD, therefore reducing the power needed to operate CheMinX. CheMinX has a silicon-drift detector (SDD) to measure fluoresced photons, enabling the quantification of major, minor, and some trace elements via XRF. XRD/XRF data are collected simultaneously in CheMinX, obviating the need for multiple compositional instruments. The CheMinX design also improves upon MSL-CheMin’s sample handling. Instead of sample cells on wheel, which are often not reusable and add complexity in commanding the instrument, CheMinX has single-use cells in a cartridge/dispenser configuration. Because of these improvements, CheMinX is an ideal instrument for Discovery-class life-detection missions, including Mars Life Explorer that was recommended for development in the Planetary Science and Astrobiology Decadal Survey 2023-2032.

E B Rampe↗

Study of Aircraft Structural Response and Occupant Loading During a Ditching Event Utilizing LS-DYNA Simulation

In this study, the capability of finite element model (FEM) analysis to assess aircraft structural response and occupant injury risk during aircraft water ditching conditions was evaluated. A FEM of the Fokker F28 aircraft, previously validated against full-scale crash test data, was simulated in a realistic water impact environment utilizing recorded conditions from the ditching of US Airways Flight 1549 into the Hudson River. The FEM of the F28 aircraft, was developed from a NASTRAN loads model provided by the vehicle manufacturer, calibrated using component fuselage drop-tests, and validated through test-analysis comparisons from a full-scale crash test of the F28 onto soil. Simulation results are presented in several categories: vehicle kinematics, structural accelerations, damage, occupant responses, and injury risk predictions. Results were consistent with the general outcomes of Flight 1549, indicating that the developed vehicle FEM, validated against land impact test data, may provide an effective tool for evaluating water ditching events.

Jacob Putnam↗

NDARC - NASA Design and Analysis of Rotorcraft: Input and Data Structures - Vol 2

The NDARC code performs design and analysis tasks. The design task involves sizing the rotorcraft to satisfy specified design conditions and missions. The analysis tasks can include off-design mission performance analysis, flight performance calculation for point operating conditions, and generation of subsystem or component performance maps. Figure 1-1 illustrates the tasks. The principal tasks (sizing, mission analysis, flight performance analysis) are shown in the figure as boxes with heavy borders. Heavy arrows show control of subordinate tasks. The aircraft description (figure 1-1) consists of all the information, input and derived, that defines the aircraft. The aircraft consists of a set of components, including fuselage, rotors, wings, tails, and propulsion. This information can be the result of the sizing task; can come entirely from input, for a fixed model; or can come from the sizing task in a previous case or previous job. The aircraft description information is available to all tasks and all solutions (indicated by light arrows). The sizing task determines the dimensions, power, and weight of a rotorcraft that can perform a specified set of design conditions and missions. The aircraft size is characterized by parameters such as design gross weight, weight empty, rotor radius, and engine power available. The relations between dimensions, power, and weight generally require an iterative solution. From the design flight conditions and missions, the task can determine the total engine power or the rotor radius (or both power and radius can be fixed), as well as the design gross weight, maximum takeoff weight, drive system torque limit, and fuel tank capacity. For each propulsion group, the engine power or the rotor radius can be sized. Missions are defined for the sizing task, and for the mission performance analysis. A mission consists of a number of mission segments, for which time, distance, and fuel burn are evaluated. For the sizing task, certain missions are designated to be used for design gross weight calculations; for transmission sizing; and for fuel tank sizing. The mission parameters include mission takeoff gross weight and useful load. For specified takeoff fuel weight with adjustable segments, the mission time or distance is adjusted so the fuel required for the mission (burned plus reserve) equals the takeoff fuel weight. The mission iteration is on fuel weight or energy. Flight conditions are specified for the sizing task, and for the flight performance analysis. For the sizing task, certain flight conditions are designated to be used for design gross weight calculations; for transmission sizing; for maximum takeoff weight calculations; and for antitorque or auxiliary thrust rotor sizing. The flight condition parameters include gross weight and useful load. For flight conditions and mission takeoff, the gross weight can be maximized, such that the power required equals the power available. A flight state is defined for each mission segment and each flight condition. The aircraft performance can be analyzed for the specified state, or a maximum effort performance can be identified. The maximum effort is specified in terms of a quantity such as best endurance or best range, and a variable such as speed, rate of climb, or altitude. The aircraft must be trimmed, by solving for the controls and motion that produce equilibrium in the specified flight state. Different trim solution definitions are required for various flight states. Evaluating the rotor hub forces may require solution of the blade flap equations of motion.

NDARC↗

Fairing Separation Analysis Using SepTOOL

This document describes the relevant equations programmed in spreadsheet software, SepTOOL, developed by ZIN Technologies, Inc. (ZIN) to determine the separation clearance between a launch vehicle payload fairing and remaining stages. The software uses closed form rigid body dynamic solutions of the vehicle in combination with flexible body dynamics of the fairing, which is obtained from flexible body dynamic analysis or from test data, and superimposes the two results to obtain minimum separation clearance for any given set of flight trajectory conditions. Using closed form solutions allows SepTOOL to perform separation calculations several orders of magnitude faster compared to numerical methods which allows users to perform real time parameter studies. Moreover, SepTOOL can optimize vehicle performance to minimize separation clearance. This tool can evaluate various shapes and sizes of fairings along with different vehicle configurations and trajectories. These geometries and parameters are inputted in a user friendly interface. Although the software was specifically developed for evaluating the separation clearance of launch vehicle payload fairings, separation dynamics of other launch vehicle components can be evaluated provided that aerodynamic loads acting on the vehicle during the separation event are negligible. This document describes the development of SepTOOL providing analytical procedure and theoretical equations whose implementation of these equations is not disclosed. Realistic examples are presented, and the results are verified with ADAMS (MSC Software Corporation) simulations. It should be noted that SepTOOL is a preliminary separation clearance assessment software for payload fairings and should not be used for final clearance analysis.

fairings↗

Aeroassist flight experiment aerodynamics and aerothermodynamics

The problem is to determine the transitional flow aerodynamics and aerothermodynamics, including the base flow characteristics, of the Aeroassist Flight Experiment (AFE). The justification for the computational fluid dynamic (CFD) Application stems from MSFC's system integration responsibility for the AFE. To insure that the AFE objectives are met, MSFC must understand the limitations and uncertainties of the design data. Perhaps the only method capable of handling the complex physics of the rarefied high energy AFE trajectory is Bird's Direct Simulation Monte Carlo (DSMC) technique. The 3-D code used in this analysis is applicable only to the AFE geometry. It uses the Variable Hard Sphere (VHS) collision model and five specie chemistry model available from Langley Research Center. The code is benchmarked against the AFE flight data and used as an Aeroassisted Space Transfer Vehicle (ASTV) design tool. The code is being used to understand the AFE flow field and verify or modify existing design data. Continued application to lower altitudes is testing the capability of the Numerical Aerodynamic Simulation Facility (NASF) to handle 3-D DSMC and its practicality as an ASTV/AFE design tool.

Brewer, Edwin B.↗

Lidar Measurements of Atmospheric CO2 From Regional to Global Scales

Atmospheric CO2 is a critical forcing for the Earth's climate and the knowledge on its distributions and variations influences predictions of the Earth's future climate. Large uncertainties in the predictions persist due to limited observations. This study uses the airborne Intensity-Modulated Continuous-Wave (IMCW) lidar developed at NASA Langley Research Center to measure regional atmospheric CO2 spatio-temporal variations. Further lidar development and demonstration will provide the capability of global atmospheric CO2 estimations from space, which will significantly advances our knowledge on atmospheric CO2 and reduce the uncertainties in the predictions of future climate. In this presentation, atmospheric CO2 column measurements from airborne flight campaigns and lidar system simulations for space missions will be discussed. A measurement precision of approx.0.3 ppmv for a 10-s average over desert and vegetated surfaces has been achieved. Data analysis also shows that airborne lidar CO2 column measurements over these surfaces agree well with in-situ measurements. Even when thin cirrus clouds present, consistent CO2 column measurements between clear and thin cirrus cloudy skies are obtained. Airborne flight campaigns have demonstrated that precise atmospheric column CO2 values can be measured from current IM-CW lidar systems, which will lead to use this airborne technique in monitoring CO2 sinks and sources in regional and continental scales as proposed by the NASA Atmospheric Carbon and Transport â€" America project. Furthermore, analyses of space CO2 measurements shows that applying the current IM-CW lidar technology and approach to space, the CO2 science goals of space missions will be achieved, and uncertainties in CO2 distributions and variations will be reduced.

Lin, Bing↗

HIFIRE Flight 2 Overview and Status Update 2011

A collaborative international effort, the Hypersonic International Flight Research Experimentation (HIFiRE) Program aims to study basic hypersonic phenomena through flight experimentation. HIFiRE Flight 2 teams the United States Air Force Research Lab (AFRL), NASA, and the Australian Defence Science and Technology Organisation (DSTO). Flight 2 will develop an alternative test technique for acquiring high enthalpy scramjet flight test data, allowing exploration of accelerating hydrocarbon-fueled scramjet performance and dual-to-scram mode transition up to and beyond Mach 8 flight. The generic scramjet flowpath is research quality and the test fuel is a simple surrogate for an endothermically cracked liquid hydrocarbon fuel. HIFiRE Flight 2 will be a first of its kind in contribution to scramjets. The HIFiRE program builds upon the HyShot and HYCAUSE programs and aims to leverage the low-cost flight test technique developed in those programs. It will explore suppressed trajectories of a sounding rocket propelled test article and their utility in studying ramjet-scramjet mode transition and flame extinction limits research. This paper describes the overall scramjet flight test experiment mission goals and objectives, flight test approach and strategy, ground test and analysis summary, development status and project schedule. A successful launch and operation will present to the scramjet community valuable flight test data in addition to a new tool, and vehicle, with which to explore high enthalpy scramjet technologies.

Jackson, Kevin R.↗

Gaussian Process for Flight Delay Prediction: Learning a Stochastic Process

This paper presents a machine-learning approach to predict flight delays. Whereas neural networks are extensively studied for predictive capabilities, they involve non-intuitive design and extensive analysis, particularly in training and optimization processes. Instead, the proposed framework employs Gaussian Processes as a supervised learning technique for flight delay prediction. This data-driven approach trains the model using prior information, specifically the mean and covariance tied to existing data. The proposed Gaussian Process Regression (GPR) model employs the day of flight as a pivotal feature for delay forecasting. We analyze flights from various routes and gauge the accuracy of the presented learning technique by comparing the predicted delays with the actual ones. Given the inherent challenges in precisely forecasting delays, we predict the delays with a 95 % confidence interval. Also, an error propagation analysis in the prediction horizon is carried out to determine the optimal time frame for prediction. The proposed method for flight delay prediction is important as airlines can strategize flight operations and issue timely advisories.

stochastic↗

Parametric Analysis of a Hover Test Vehicle using Advanced Test Generation and Data Analysis

Large complex aerospace systems are generally validated in regions local to anticipated operating points rather than through characterization of the entire feasible operational envelope of the system. This is due to the large parameter space, and complex, highly coupled nonlinear nature of the different systems that contribute to the performance of the aerospace system. We have addressed the factors deterring such an analysis by applying a combination of technologies to the area of flight envelop assessment. We utilize n-factor (2,3) combinatorial parameter variations to limit the number of cases, but still explore important interactions in the parameter space in a systematic fashion. The data generated is automatically analyzed through a combination of unsupervised learning using a Bayesian multivariate clustering technique (AutoBayes) and supervised learning of critical parameter ranges using the machine-learning tool TAR3, a treatment learner. Covariance analysis with scatter plots and likelihood contours are used to visualize correlations between simulation parameters and simulation results, a task that requires tool support, especially for large and complex models. We present results of simulation experiments for a cold-gas-powered hover test vehicle.

Gundy-Burlet, Karen↗

Analysis of Free-Flight Laminar, Transitional, and Turbulent Heat-Transfer Results at Free-Stream Mach Numbers Near 20 (Reentry F)

Laminar, transitional, and turbulent heat-transfer data were measured during a reentry flight at a Mach number of 20 on a 5 deg half-angle cone 3.962 m (13 ft) long with an initial nose tip radius of 0.254 cm (0.1 in.). The free-stream Reynolds number increased during the prime data period from 7.0 x 10(exp 6) to 51.5 x 10(exp 6) per meter (2.1 x 10(exp 6) to 15.7 x 10(exp 6) per foot) and the ratio of wall to total temperature varied from 0.053 to 0.12. The angle of attack was less than 1deg for the prime data period. The experimental laminar and turbulent heating rates are compared with results from existing flat-plate prediction methods. At conditions of minimal tip blunting and angle of attack (above 26.8 km (88 000 ft)), values from a flat-plate laminar method agreed within 20 percent with the laminar data. The Schultz-Grunow skin-friction equation with reference enthalpy; conditions, with the Reynolds number based on distance from the transition location, and with the Colburn Reynolds analogy agreed within 10 percent with the experimental turbuleiit heating data. The Van Driest n skin-friction equation with Reynolds number greater than 10(exp 7) based on distance from the peak heating point and the Colburn Reynolds analogy was also within approximately 10 percent of the experimental turbulent heating data. A data correlation jbf the extent of transition and a simple empirical transition-zone heating correlation were also presented.

Zoby, Ernest V.↗

Spectral Analysis of the Primary Flight Focal Plane Arrays for the Thermal Infrared Sensor

Thermal Infrared Sensor (TIRS) is a (1) New longwave infrared (10 - 12 micron) sensor for the Landsat Data Continuity Mission, (2) 185 km ground swath; 100 meter pixel size on ground, (3) Pushbroom sensor configuration. Issue of Calibration are: (1) Single detector -- only one calibration, (2) Multiple detectors - unique calibration for each detector -- leads to pixel-to-pixel artifacts. Objectives are: (1) Predict extent of residual striping when viewing a uniform blackbody target through various atmospheres, (2) Determine how different spectral shapes affect the derived surface temperature in a realistic synthetic scene.

Montanaro, Matthew↗

Orbit Determination Toolbox

The Orbit Determination Toolbox is an orbit determination (OD) analysis tool based on MATLAB and Java that provides a flexible way to do early mission analysis. The toolbox is primarily intended for advanced mission analysis such as might be performed in concept exploration, proposal, early design phase, or rapid design center environments. The emphasis is on flexibility, but it has enough fidelity to produce credible results. Insight into all flight dynamics source code is provided. MATLAB is the primary user interface and is used for piecing together measurement and dynamic models. The Java Astrodynamics Toolbox is used as an engine for things that might be slow or inefficient in MATLAB, such as high-fidelity trajectory propagation, lunar and planetary ephemeris look-ups, precession, nutation, polar motion calculations, ephemeris file parsing, and the like. The primary analysis functions are sequential filter/smoother and batch least-squares commands that incorporate Monte-Carlo data simulation, linear covariance analysis, measurement processing, and plotting capabilities at the generic level. These functions have a user interface that is based on that of the MATLAB ODE suite. To perform a specific analysis, users write MATLAB functions that implement truth and design system models. The user provides his or her models as inputs to the filter commands. The software provides a capability to publish and subscribe to a software bus that is compliant with the NASA Goddard Mission Services Evolution Center (GMSEC) standards, to exchange data with other flight dynamics tools to simplify the flight dynamics design cycle. Using the publish and subscribe approach allows for analysts in a rapid design center environment to seamlessly incorporate changes in spacecraft and mission design into navigation analysis and vice versa.

Carpenter, James R.↗

Development of flight experiment task requirements. Volume 2: Technical Report. Part 2: Appendix H: Tasks-skills data series

The data sheets presented contain the results of the task analysis portion of the study to identify skill requirements of space shuttle crew personnel. A comprehensive data base is provided of crew functions, operating environments, task dependencies, and task-skills applicable to a representative cross section of earth orbital research experiments.

Hatterick, G. R.↗

Analysis and Monte Carlo simulation of near-terminal aircraft flight paths

The flight paths of arriving and departing aircraft at an airport are stochastically represented. Radar data of the aircraft movements are used to decompose the flight paths into linear and curvilinear segments. Variables which describe the segments are derived, and the best fitting probability distributions of the variables, based on a sample of flight paths, are found. Conversely, given information on the probability distribution of the variables, generation of a random sample of flight paths in a Monte Carlo simulation is discussed. Actual flight paths at Dulles International Airport are analyzed and simulated.

Schiess, J. R.↗

Radiometric calibration analysis of SIR-B imagery

The second flight of the NASA Spaceborne Imaging Radar (SIR-B) collected nearly 8 hours of digital synthetic-aperture radar (SAR) data of the earth's surface. This paper analyzes the performance of the SAR to determine the accuracy of the relative radiometric calibration of these data. Procedures are presented for deriving accuracy estimates as well as limitations under which these estimates are valid. The impact on calibration of an RF breakdown in the primary antenna feed system cable is evaluated. An analysis of the platform stability based on the SAR echo data is also presented in conjunction with its resultant effect on the calibration accuracy. Finally, numerical error bounds are derived with guidelines on their utilization.

Wall, Stephen D.↗

Design and Control of an Experimental Tilt-Wing Aircraft

In this project, work has been done in the field of conceptual design of experimental tiltrotors. The main tools that have been used are NDARC (NASA Design and Analysis of Rotorcraft) and SIMPLI-FLYD. NDARC is a conceptual design tool for rotorcraft, and it is used to find trim points under various flight conditions. SIMPLI-FLYD is an integrated collection of software tools that enables a flight dynamics and control assessment of the rotorcraft vehicle design generated from NDARC. Two different tiltrotors have been investigated. Initially, work was done with the Bell XV- 15 tiltrotor. NDARCs ability to correctly model the tiltwing transition between airplane mode and hover mode was looked into. In addition, data from old flight tests were compared to the NDARC output, to see how accurately performance could be predicted. After the XV-15 analysis, an NDRARC model of a novel tiltwing concept from Elytron Aircraft was written and analyzed together with SIMPLI-FLYD. Elytron 2S is an experimental tiltwing aircraft, consisting of a joined-wing design with a small central wing for the proprotor. An alternative approach to hover control is used, where the typical rotor hub and swash plate are substituted for linear actuators controlling pitch, yaw and roll. The objective with the analysis of Elytron is to obtain a more complete understanding of the maneuverability and possible performance of this alternative aircraft configuration.

Conceptual Design↗

Dragonfly Rotor Optimization using Machine Learning Applied to an OVERFLOW Generated Airfoil Database

NASA’s 4th New Frontiers Mission is the Titan Dragonfly relocatable lander. This coaxial quadrotor vehicle will be launched on a rocket to Titan in 2028. Following a gravity assisted Earth flyby and an approximate 6-year transit, Dragonfly will enter the Titan atmosphere around 2034 with the goal of exploring Titan’s pre-biotic chemistry and habitability. The multirotor design for this unique application has continually evolved since 2016 with constraints such as Titan’s cryogenic atmosphere at 95 Kelvin (-288 F), gravity 14% that of Earth’s, atmospheric density 440% of standard sea-level air, and the inability to test the entire system together under all these conditions until the first flight on Titan. This paper focuses on rotor design aspects of the Dragonfly lander and introduces a novel framework for multirotor design optimization considering multiple flight conditions. The methodology leverages machine learning methods and is demonstrated in the context of Dragonfly. A new OVERFLOW Machine Learning Airfoil Performance (PALMO) database is first presented. PALMO is then wrapped inside a Bayesian optimization framework and applied to a 4-rotor system (one side of the Dragonfly lander). Training data is generated on each iteration of the optimization using the CAMRAD-II comprehensive analysis software to evaluate successive rotor designs in multiple relevant flight conditions. An optimal design for the 4-rotor system was found with approximately 900 rotor designs analyzed in CAMRAD-II, which required 9 million queries of the PALMO surrogate models. This demonstration case evaluated 10,000,000 potential candidate rotor designs in 5.5 hours on 114 CPU cores using uniform inflow, and in 27.8 hours using the prescribed wake model. This work thus enables mid-fidelity rotor design optimization without requiring access to high-performance computing.

Dragonfly↗