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At least 271 records · Page 15

An Object-Oriented Interface to the CCSDS Ground Telecommand Services

The Telecommand Data Routing and Channel Services defined by the Consultative Committee for Space Data Systems (CCSDS) are flexible enough to support a myriad of commanding models. Because the standard is so broad, the traditional approach has been to implement only the portion of the standard needed by the particular spacecraft being tested/operated. Tasked with providing Telecommand Services for an entire class of spacecraft, where each spacecraft may choose any valid CCSDS commanding model, NASA Code 584 designed a common architecture capable of handling the full CCSDS protocol. The solution uses another CCSDS standard - the Standard Formatted Data Unit (SFDU) as the interface to the Telecommand Services. SFDUs provide a consistent way of labelling data objects, as well as allowing data objects to encapsulate other data objects. The resulting interface is: - Flexible: The full Data Routing and Channel Services are available via a single interface. The client (i.e. the command source) may enter commands at any layer within the protocol stack, specify any of the data aggregation or segmentation methods, and dynamically set any configuration parameter defined in the standard. - Object-oriented: Each object specifies both the data and the actions to be performed with the data. An object may contain other objects. - Expandable: New capabilities are added by defining new objects. Objects pass thru the protocol layers until they reach the applicable layer. The resulting design is: - Modular: The logic for each protocol layer is contained in a separate Application Program Interface (API). The objects used for the external interface are also used for communication between layers. - Distributable: The design can be split along any layer boundary for distribution across multiple machines. The objects ensure data consistency across platforms. This paper describes the SFDU-based interface and the resulting protocol implementation. The implementation is currently used by NASA (National Aeronautics and Space Administration) for integration & test of the microwave Anisotropy Probe (MAP) and Earth observer-I (EO-l) spacecraft. It will be used for post-launch operations of these spacecraft as well as the Imager for Magnetopause to Aurora Global Exploration (IMAGE) spacecraft.

Ray, Timothy Joseph↗

Best Practices for Crash Modeling and Simulation

Aviation safety can be greatly enhanced by the expeditious use of computer simulations of crash impact. Unlike automotive impact testing, which is now routine, experimental crash tests of even small aircraft are expensive and complex due to the high cost of the aircraft and the myriad of crash impact conditions that must be considered. Ultimately, the goal is to utilize full-scale crash simulations of aircraft for design evaluation and certification. The objective of this publication is to describe "best practices" for modeling aircraft impact using explicit nonlinear dynamic finite element codes such as LS-DYNA, DYNA3D, and MSC.Dytran. Although "best practices" is somewhat relative, it is hoped that the authors' experience will help others to avoid some of the common pitfalls in modeling that are not documented in one single publication. In addition, a discussion of experimental data analysis, digital filtering, and test-analysis correlation is provided. Finally, some examples of aircraft crash simulations are described in several appendices following the main report.

Fasanella, Edwin L.↗

The microwave spectrum and nature of the subsurface of Mars.

Expected microwave spectra of Mars are computed using an improved thermal model and accurate aspect geometry. It is found that when seasonal polar cap effects are included in the calculations, the observable spectrum of Mars is flat from 0.1-21 cm to within the accuracy of present data. The spectra obtained from this model are consistent with all the data and are obtainable from a relatively simple model (homogeneous, dry, smooth dielectric sphere). This result differs from that predicted by the analytical theory in common use which is in apparent conflict with the observed spectra. A range of electrical loss tangents, covering the extreme limits for likely dry particulate geological materials, is employed. The case of a lunar-like subsurface is completely consistent with all present data.

Cuzzi, J. N.↗

Cloud Computing for Mission Design and Operations

The space mission design and operations community already recognizes the value of cloud computing and virtualization. However, natural and valid concerns, like security, privacy, up-time, and vendor lock-in, have prevented a more widespread and expedited adoption into official workflows. In the interest of alleviating these concerns, we propose a series of guidelines for internally deploying a resource-oriented hub of data and algorithms. These guidelines provide a roadmap for implementing an architecture inspired in the cloud computing model: associative, elastic, semantical, interconnected, and adaptive. The architecture can be summarized as exposing data and algorithms as resource-oriented Web services, coordinated via messaging, and running on virtual machines; it is simple, and based on widely adopted standards, protocols, and tools. The architecture may help reduce common sources of complexity intrinsic to data-driven, collaborative interactions and, most importantly, it may provide the means for teams and agencies to evaluate the cloud computing model in their specific context, with minimal infrastructure changes, and before committing to a specific cloud services provider.

cloud computing↗

Materials Outgassing Rate Decay in Vacuum at Isothermal Conditions

As a laboratory for scientific research, the International Space Station has been in Low Earth Orbit for nearly 20 years and is expected to be on-orbit for another 10 years. The ISS has been maintaining a relatively pristine contamination environment for science payloads. Materials outgassing induced contamination is currently the dominant source for sensitive surfaces on ISS and modeling the outgassing rate decay over a 20 to 30 year period is challenging. Materials outgassing is described herein as a diffusion-reaction process using ASTM E 1559 rate data. The observation of -1/2 (diffusion) or non-integers (reaction limited) as rate decay exponents for common ISS materials indicate classical reaction kinetics is unsatisfactory in modeling materials outgassing. Non-randomness of reactant concentrations at the interface is the source of this deviation from classical reaction kinetics. A diffusion limited decay was adopted as the result of the correlation of the contaminant layer thicknesses on returned ISS hardware, the existence of high outgassing silicone exhibiting near diffusion limited decay, and the confirmation of non-depleted material after ten years in the Low Earth Orbit.Keywords: Materials Outgassing, ASTM E 1559, Reaction Kinetics, Diffusion, Space Environments Effects, Contamination

Huang, Alvin Y.↗

Summary of Data from the Sixth AIAA CFD Drag Prediction Workshop: CRM Cases 2 to 5

Results from the Sixth AIAA CFD Drag Prediction Workshop Common Research Model Cases 2 to 5 are presented. As with past workshops, numerical calculations are performed using industry-relevant geometry, methodology, and test cases. Cases 2 to 5 focused on force/moment and pressure predictions for the NASA Common Research Model wing-body and wing-body-nacelle-pylon configurations, including Case 2 - a grid refinement study and nacelle-pylon drag increment prediction study; Case 3 - an angle-of-attack buffet study; Case 4 - an optional wing-body grid adaption study; and Case 5 - an optional wing-body coupled aero-structural simulation. The Common Research Model geometry differed from previous workshops in that it was deformed to the appropriate static aeroelastic twist and deflection at each specified angle-of-attack. The grid refinement study used a common set of overset and unstructured grids, as well as user created Multiblock structured, unstructured, and Cartesian based grids. For the supplied common grids, six levels of refinement were created resulting in grids ranging from 7x10(exp 6) to 208x10(exp 6) cells. This study (Case 2) showed further reduced scatter from previous workshops, and very good prediction of the nacelle-pylon drag increment. Case 3 studied buffet onset at M=0.85 using the Medium grid (20 to 40x10(exp 6) nodes) from the above described sequence. The prescribed alpha sweep used finely spaced intervals through the zone where wing separation was expected to begin. Although the use of the prescribed aeroelastic twist and deflection at each angle-of-attack greatly improved the wing pressure distribution agreement with test data, many solutions still exhibited premature flow separation. The remaining solutions exhibited a significant spread of lift and pitching moment at each angle-of-attack, much of which can be attributed to excessive aft pressure loading and shock location variation. Four Case 4 grid adaption solutions were submitted. Starting with grids less than 2x10(exp 6) grid points, two solutions showed a rapid convergence to an acceptable solution. Four Case 5 coupled aerostructural solutions were submitted. Both showed good agreement with experimental data. Results from this workshop highlight the continuing need for CFD improvement, particularly for conditions with significant flow separation. These comparisons also suggest the need for improved experimental diagnostics to guide future CFD development.

Tinoco, Edward N.↗

A Community Convention for Ecological Forecasting: Output Files and Metadata Version 1.0

This paper summarizes the open community conventions developed by the Ecological Forecasting Initiative (EFI) for the common formatting and archiving of ecological forecasts and the metadata associated with these forecasts. Such open standards are intended to promote interoperability and facilitate forecast communication, distribution, validation, and synthesis. For output files, we first describe the convention conceptually in terms of global attributes, forecast dimensions, forecasted variables, and ancillary indicator variables. We then illustrate the application of this convention to the two file formats that are currently preferred by the EFI, netCDF (network common data form), and comma-separated values (CSV), but note that the convention is extensible to future formats. For metadata, EFI's convention identifies a subset of conventional metadata variables that are required (e.g., temporal resolution and output variables) but focuses on developing a framework for storing information about forecast uncertainty propagation, data assimilation, and model complexity, which aims to facilitate cross-forecast synthesis. The initial application of this convention expands upon the Ecological Metadata Language (EML), a commonly used metadata standard in ecology. To facilitate community adoption, we also provide a Github repository containing a metadata validator tool and several vignettes in R and Python on how to both write and read in the EFI standard. Lastly, we provide guidance on forecast archiving, making an important distinction between short-term dissemination and long-term forecast archiving, while also touching on the archiving of code and workflows. Overall, the EFI convention is a living document that can continue to evolve over time through an open community process.

Michael C. Dietze↗

Sequence data - Magnitude and implications of some ambiguities.

A stochastic model is applied to the divergence of the horse-pig lineage from a common ansestor in terms of the alpha and beta chains of hemoglobin and fibrinopeptides. The results are compared with those based on the minimum mutation distance model of Fitch (1972). Buckwheat and cauliflower cytochrome c sequences are analyzed to demonstrate their ambiguities. A comparative analysis of evolutionary rates for various proteins of horses and pigs shows that errors of considerable magnitude are introduced by Glx and Asx ambiguities into evolutionary conclusions drawn from sequences of incompletely analyzed proteins.

Holmquist, R.↗

Variational data assimilation with a semi-Lagrangian semi-implicit global shallow-water equation model and its adjoint

An adjoint model is developed for variational data assimilation using the 2D semi-Lagrangian semi-implicit (SLSI) shallow-water equation global model of Bates et al. with special attention being paid to the linearization of the interpolation routines. It is demonstrated that with larger time steps the limit of the validity of the tangent linear model will be curtailed due to the interpolations, especially in regions where sharp gradients in the interpolated variables coupled with strong advective wind occur, a synoptic situation common in the high latitudes. This effect is particularly evident near the pole in the Northern Hemisphere during the winter season. Variational data assimilation experiments of 'identical twin' type with observations available only at the end of the assimilation period perform well with this adjoint model. It is confirmed that the computational efficiency of the semi-Lagrangian scheme is preserved during the minimization process, related to the variational data assimilation procedure.

Li, Y.↗

MLtool: Universal Supervised Machine Learning Tool to Model Tabulated Data

Machine Learning (ML) is a subfield of Artificial Intelligence that gives computers the ability to learn from past data without being explicitly programmed. The predictive capabilities of ML models have already been used to facilitate several scientific breakthroughs. However, the practical application of ML is often limited due to the gaps in technical knowledge of its users. The common issue faced by many scientific researchers is the inability to choose the appropriate ML pipelines that are needed to treat real-world data, which is often sparse and noisy. To solve this problem, we have developed an automated Machine Learning tool (MLtool) that includes a set of ML algorithms and approaches to aid scientific researchers. The current version of MLtool is implemented as an object-oriented Python code that is easily extensible. It includes 44 different regression algorithms used to model data. MLtool helps users select the best model for their data, based on the scoring metrics used. Besides regression algorithms, MLtool also includes a suite of pre- and post-processing techniques such as missing value imputation, categorical variable encoding, input feature normalization, uncertainty quantification, exploratory data analysis (EDA), etc. MLtool was tested on several publicly available multi-dimensional data sets and was found capable of making accurate predictions.

Machine learning↗

MLtool Python Code

Machine Learning (ML) is a subfield of Artificial Intelligence that gives computers the ability to learn from past data without being explicitly programmed. The predictive capabilities of ML models have already been used to facilitate several scientific breakthroughs. However, the practical application of ML is often limited due to the gaps in technical knowledge of its users. The common issue faced by many scientific researchers is the inability to choose the appropriate ML pipelines that are needed to treat real-world data, which is often sparse and noisy. To solve this problem, we have developed an automated Machine Learning tool (MLtool) that includes a set of ML algorithms and approaches to aid scientific researchers. The current version of MLtool is implemented as an object-oriented Python code that is easily extensible. It includes 44 different regression algorithms used to model data. MLtool helps users select the best model for their data, based on the scoring metrics used. Besides regression algorithms, MLtool also includes a suite of pre- and post-processing techniques such as missing value imputation, categorical variable encoding, input feature normalization, uncertainty quantification, exploratory data analysis (EDA), etc. MLtool was tested on several publicly available multi-dimensional data sets and was found capable of making accurate predictions.

Machine Learning↗

Spatial validation reveals poor predictive performance of large-scale ecological mapping models

Mapping aboveground forest biomass is central for assessing the global carbon balance. However, current large-scale maps show strong disparities, despite good validation statistics of their underlying models. Here, we attribute this contradiction to a flaw in the validation methods, which ignore spatial autocorrelation (SAC) in data, leading to overoptimistic assessment of model predictive power. To illustrate this issue, we reproduce the approach of large-scale mapping studies using a massive forest inventory dataset of 11.8 million trees in central Africa to train and validate a random forest model based on multispectral and environmental variables. A standard nonspatial validation method suggests that the model predicts more than half of the forest biomass variation, while spatial validation methods accounting for SAC reveal quasi-null predictive power. This study underscores how a common practice in big data mapping studies shows an apparent high predictive power, even when predictors have poor relationships with the ecological variable of interest, thus possibly leading to erroneous maps and interpretations.

biomass↗

An interactive environment for the analysis of large Earth observation and model data sets

We propose to develop an interactive environment for the analysis of large Earth science observation and model data sets. We will use a standard scientific data storage format and a large capacity (greater than 20 GB) optical disk system for data management; develop libraries for coordinate transformation and regridding of data sets; modify the NCSA X Image and X Data Slice software for typical Earth observation data sets by including map transformations and missing data handling; develop analysis tools for common mathematical and statistical operations; integrate the components described above into a system for the analysis and comparison of observations and model results; and distribute software and documentation to the scientific community.

Bowman, Kenneth P.↗

An interactive environment for the analysis of large Earth observation and model data sets

We propose to develop an interactive environment for the analysis of large Earth science observation and model data sets. We will use a standard scientific data storage format and a large capacity (greater than 20 GB) optical disk system for data management; develop libraries for coordinate transformation and regridding of data sets; modify the NCSA X Image and X DataSlice software for typical Earth observation data sets by including map transformations and missing data handling; develop analysis tools for common mathematical and statistical operations; integrate the components described above into a system for the analysis and comparison of observations and model results; and distribute software and documentation to the scientific community.

Bowman, Kenneth P.↗

Extensions to the Dynamic Aerospace Vehicle Exchange Markup Language

The Dynamic Aerospace Vehicle Exchange Markup Language (DAVE-ML) is a syntactical language for exchanging flight vehicle dynamic model data. It provides a framework for encoding entire flight vehicle dynamic model data packages for exchange and/or long-term archiving. Version 2.0.1 of DAVE-ML provides much of the functionality envisioned for exchanging aerospace vehicle data; however, it is limited in only supporting scalar time-independent data. Additional functionality is required to support vector and matrix data, abstracting sub-system models, detailing dynamics system models (both discrete and continuous), and defining a dynamic data format (such as time sequenced data) for validation of dynamics system models and vehicle simulation packages. Extensions to DAVE-ML have been proposed to manage data as vectors and n-dimensional matrices, and record dynamic data in a compatible form. These capabilities will improve the clarity of data being exchanged, simplify the naming of parameters, and permit static and dynamic data to be stored using a common syntax within a single file; thereby enhancing the framework provided by DAVE-ML for exchanging entire flight vehicle dynamic simulation models.

Brian, Geoffrey J.↗

An aircraft model for the AIAA controls design challenge

A generic, state-of-the-art, high-performance aircraft model, including detailed, full-envelope, nonlinear aerodynamics, and full-envelope thrust and first-order engine response data is described. While this model was primarily developed Controls Design Challenge, the availability of such a model provides a common focus for research in aeronautical control theory and methodology. An implementation of this model using the FORTRAN computer language, associated routines furnished with the aircraft model, and techniques for interfacing these routines to external procedures is also described. Figures showing vehicle geometry, surfaces, and sign conventions are included.

Brumbaugh, Randal W.↗

SEL Ada reuse analysis and representations

Overall, it was revealed that the pattern of Ada reuse has evolved from initial reuse of utility components into reuse of generalized application architectures. Utility components were both domain-independent utilities, such as queues and stacks, and domain-specific utilities, such as those that implement spacecraft orbit and attitude mathematical functions and physics or astronomical models. The level of reuse was significantly increased with the development of a generalized telemetry simulator architecture. The use of Ada generics significantly increased the level of verbatum reuse, which is due to the ability, using Ada generics, to parameterize the aspects of design that are configurable during reuse. A key factor in implementing generalized architectures was the ability to use generic subprogram parameters to tailor parts of the algorithm embedded within the architecture. The use of object oriented design (in which objects model real world entities) significantly improved the modularity for reuse. Encapsulating into packages the data and operations associated with common real world entities creates natural building blocks for reuse.

Kester, Rush↗

Faulty behavior of asynchronous storage elements

It is often assumed that the faults in storage elements (SE's) can be modeled as output/input stuck-at-faults of the element. They are implicitly considered equivalent to the stuck-at faults in the combinational logic surrounding the SE cells. A more accurate higher level fault model for elementary SE's used in asynchronous circuits is presented. This model offers better representation of the physical failures. It is shown that the stuck-at model may be adequate if only modest fault coverage is desired. The enhanced model includes some common fault behaviors of SE's that are not covered by the stuck-at model. These include data-feed-through behaviors that cause the SE to be combinational. Fault models for complex SE cells can be obtained without a significant loss of information about the structure of the circuit.

Al-Assadi, Waleed K.↗