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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 163 records · Page 9

Validation and Verification of LADEE Models and Software

The Lunar Atmosphere Dust Environment Explorer (LADEE) mission will orbit the moon in order to measure the density, composition and time variability of the lunar dust environment. The ground-side and onboard flight software for the mission is being developed using a Model-Based Software methodology. In this technique, models of the spacecraft and flight software are developed in a graphical dynamics modeling package. Flight Software requirements are prototyped and refined using the simulated models. After the model is shown to work as desired in this simulation framework, C-code software is automatically generated from the models. The generated software is then tested in real time Processor-in-the-Loop and Hardware-in-the-Loop test beds. Travelling Road Show test beds were used for early integration tests with payloads and other subsystems. Traditional techniques for verifying computational sciences models are used to characterize the spacecraft simulation. A lightweight set of formal methods analysis, static analysis, formal inspection and code coverage analyses are utilized to further reduce defects in the onboard flight software artifacts. These techniques are applied early and often in the development process, iteratively increasing the capabilities of the software and the fidelity of the vehicle models and test beds.

Gundy-Burlet, Karen↗

MBSE Validation and Verification: Case Study for LADEE

The Lunar Atmosphere Dust Environment Explorer (LADEE) mission orbited the moon in order to measure the density, composition, and time variability of the lunar dust environment. The successful mission launched September 7, 2013 and was de-orbited and impacted the moon's surface on April 17, 2014. The ground-side and onboard flight software for the mission was developed using a “Model-Based Software Engineering” (MBSE) methodology combined with strong reuse of Government and Commercial Off-The Shelf (G/COTS) components. Models of the spacecraft and flight software were developed in a graphical dynamics modeling package. Flight Software requirements were prototyped and refined using the simulated models. After the model was shown to work as desired in the simulation framework, C-code software was automatically generated from the models. The auto-generated software was then tested in real-time Processor-in-the-Loop and Hardware-in-the-Loop test beds. “Traveling Road Show” test beds were used for early integration tests with payloads and other subsystems. Traditional techniques for verifying computational sciences models were used to characterize the spacecraft simulation. A lightweight set of formal methods analysis, static analysis, formal inspection, and code coverage analyses were utilized to further reduce defects in the onboard flight software artifacts. These techniques were applied early and often in the development process, iteratively increasing the capabilities of software and fidelity of vehicle models and test beds.

Model-Based Software Engineering, Validation and V↗

Community Solar Project Models: An Introduction to Basic Financial and Administrative Relationships [Slides]

This resource is a collection of visual aids and descriptions to help explain the basic financial and administrative relationships underpinning common community solar project models. The graphics in this resource depict the flow of electricity from generation to consumption and the financial exchanges between the community solar project owner, subscribers, and distribution utility. Community solar models vary based on ownership (e.g., third party, utility), customer type (e.g., multifamily, single-household), and solar array location (e.g., on-site, off-site).

14 SOLAR ENERGY↗

Piloted Full-Motion Simulation with Simulink®

A recent experiment at NASA Ames Research Center’s Vertical Motion Simulator (VMS) successfully combined a real-time, human in-the-loop architecture with the flexibility of operating in the Simulink® graphical model-based engineering environment. The VMS is a large amplitude flight simulator designed to be adaptable to provide rapid integration and development of a wide variety of vehicles and support diverse aeronautical investigations. Math models are often programmed in Simulink. Typically, to run Simulink models in real time, they are converted to C code. However, the conversion and integration process can be time consuming and cumbersome. Thus, the VMS facility capabilities were expanded to allow a Simulink vehicle math model to run in the MathWorks’ MATLAB environment during a piloted full-motion simulation experiment. The MATLAB Simulink based approach to driving the VMS was found to decrease development time by allowing quick integration of math model changes and providing the ability to run the same version of the model on researcher’s desktop computers. This accomplishment demonstrated that the development ease of the graphical Simulink environment could be retained, while working within the real-time environment of the VMS architecture and maintaining the unique flexibility of the VMS.

hardware in-the-loop↗

An improvement in the numerical integration procedure used in the NASA Marshall engineering thermosphere model

A proposed replacement scheme for the integration of the barometric and diffusion equations in the NASA Marshall Engineering Thermosphere (MET) model is presented. This proposed integration scheme is based on Gaussian Quadrature. Extensive numerical testing reveals it to be faster, more accurate and more reliable than the present integration scheme (a modified form of Simpson's Rule) used in the MET model. Numerous graphical examples are provided, along with a listing of a modified form of the MET model in which subroutine INTEGRATE (using Simpson's Rule) is replaced by subroutine GAUSS (which uses Gaussian Quadrature). It is recommended that the Gaussian Quadrature integration scheme, as used here, be used in the MET model.

Hickey, Michael Philip↗

Piloted Full-Motion Simulation in Simulink®

A recent experiment at NASA Ames Research Center’s Vertical Motion Simulator (VMS) successfully combined a real-time, human in-the-loop architecture with the flexibility of operating in the Simulink® graphical model-based engineering environment. The VMS is a large amplitude flight simulator designed to be adaptable to provide rapid integration and development of a wide variety of vehicles and support diverse aeronautical investigations. Math models are often programmed in Simulink. Typically, to run Simulink models in real time, they are converted to C code. However, the conversion and integration process can be time consuming and cumbersome. Thus, the VMS facility capabilities were expanded to allow a Simulink vehicle math model to run in the MathWorks’ MATLAB environment during a piloted full-motion simulation experiment. The MATLAB Simulink based approach to driving the VMS was found to decrease development time by allowing quick integration of math model changes and providing the ability to run the same version of the model on researcher’s desktop computers. This accomplishment demonstrated that the development ease of the graphical Simulink environment could be retained, while working within the real-time environment of the VMS architecture and maintaining the unique flexibility of the VMS.

Lewis, Emily K.↗

Integrated modeling tool for performance engineering of complex computer systems

This report summarizes Advanced System Technologies' accomplishments on the Phase 2 SBIR contract NAS7-995. The technical objectives of the report are: (1) to develop an evaluation version of a graphical, integrated modeling language according to the specification resulting from the Phase 2 research; and (2) to determine the degree to which the language meets its objectives by evaluating ease of use, utility of two sets of performance predictions, and the power of the language constructs. The technical approach followed to meet these objectives was to design, develop, and test an evaluation prototype of a graphical, performance prediction tool. The utility of the prototype was then evaluated by applying it to a variety of test cases found in the literature and in AST case histories. Numerous models were constructed and successfully tested. The major conclusion of this Phase 2 SBIR research and development effort is that complex, real-time computer systems can be specified in a non-procedural manner using combinations of icons, windows, menus, and dialogs. Such a specification technique provides an interface that system designers and architects find natural and easy to use. In addition, PEDESTAL's multiview approach provides system engineers with the capability to perform the trade-offs necessary to produce a design that meets timing performance requirements. Sample system designs analyzed during the development effort showed that models could be constructed in a fraction of the time required by non-visual system design capture tools.

Wright, Gary↗

Direction of impact for explainable risk assessment modeling

Abstract Several graphical indicators have been recently introduced to help analysts visualize the marginal effects of inputs in complex models. The insights derived from such tools may help decision‐makers and risk analysts in designing interventions. However, we know little about the adequacy and consistency of different indicators. This work investigates popular marginal effect indicators to understand whether they yield indications consistent with the properties of the quantitative model under inspection. Specifically, we examine the notions of monotonicity, Lipschitz, and concavity consistency. Surprisingly, only PD functions satisfy all these notions of consistency. However, when selecting the indicators, in addition to consistency, analysts need to consider the risk of model extrapolation. For situations where such risk is under control, we utilize individual conditional expectations together with PD plots. Two applications, on a NASA space risk assessment model and a susceptible exposed infected recovered (SEIR) model for the COVID‐19 pandemic illustrate the insights obtained from these indicators.

Mathematical Methods In Social Sciences↗

The Effect of the Prior and the Experimental Design on the Inference of the Precision Matrix in Gaussian Chain Graph Models

Here, we investigate whether (and how) experimental design could aid in the estimation of the precision matrix in a Gaussian chain graph model, especially the interplay between the design, the effect of the experiment and prior knowledge about the effect. Estimation of the precision matrix is a fundamental task to infer biological graphical structures like microbial networks. We compare the marginal posterior precision of the precision matrix under four priors: flat, conjugate Normal-Wishart, Normal-MGIG and a general independent. Under the flat and conjugate priors, the Laplace-approximated posterior precision is not a function of the design matrix rendering useless any efforts to find an optimal experimental design to infer the precision matrix. In contrast, the Normal-MGIG and general independent priors do allow for the search of optimal experimental designs, yet there is a sharp upper bound on the information that can be extracted from a given experiment. We confirm our theoretical findings via a simulation study comparing (i) the KL divergence between prior and posterior and (ii) the Stein’s loss difference of MAPs between random and no experiment. Our findings provide practical advice for domain scientists conducting experiments to better infer the precision matrix as a representation of a biological network.

54 ENVIRONMENTAL SCIENCES↗

Heliophysical Modeling at the CCMC - Community Modeling Activities to Compliment the VHGO

The Community Coordinated Modeling Center (CCMC) hosts an ever growing inventory of models to support the research activities of the Heliophysics community.In this poster we detail this model inventory. We describe the manner in which the CCMC provides access to these models to the community. This support includes model runs driven with archived data and 'realtime' runs which update as the latest data is ingested by the models. It includes runs for individual researchers and in support of observational planning and analysis for a number of flight missions. Our need to integrate the data streams into and out of numerous models and graphics packages has led to the development of a number of infra-structure component that are also highly relevant to the design of the VHGO. We discuss this issue and the natural and vital link that must develop between the VHGO and modeling centers such as the CCMC, if the usefulness of the VHGO is to be maximized.

MacNeice, P.↗

User's instructions for the GE cardiovascular model to simulate LBNP and tilt experiments, with graphic capabilities

The present form of this cardiovascular model simulates both 1-g and zero-g LBNP (lower body negative pressure) experiments and tilt experiments. In addition, the model simulates LBNP experiments at any body angle. The model is currently accessible on the Univac 1110 Time-Shared System in an interactive operational mode. Model output may be in tabular form and/or graphic form. The graphic capabilities are programmed for the Tektronix 4010 graphics terminal and the Univac 1110.

Source record↗

A Misperception in Reliability Growth Modelling

The Duane reliability growth model is n(t)/t = k t^-alpha (1) The reliability growth rate is alpha, the downward slope of n(t)/t versus t. It usually varies from 0.2 to 0.6. k is a constant. Crow used a 56-failure data set to illustrate reliability growth.1 A graphical Duane model fit to this data gives n(t)/t = 0.640 t^-0.283 (2) A problem in using the Duane-Crow reliability growth model is that it assumes that reliability growth continues and the failure rate decreases throughout the test period. It is more usual that reliability growth stops when the failure rated is low enough. Growth testing is often followed by testing with a low constant failure rate due to rare or uncorrectable failure modes. As more and more low constant rate acceptable failures accumulate after the period of reliability growth, the reliability growth time exponent alpha decreases toward zero. This occurs if constant rate failures are treated as occurring during the reliability growth period. It is more accurate to model a period of initial reliability growth followed by testing without repair to more accurately determine the final constant failure rate. This is done in the abcd model. n(t)/t = a t^-b + c from t = 0 to td (3) = c + d after td, where d = a td^-b (4) The term a t^-b describes the continuous reliability growth that continues out to time td and c is the constant uncorrected failure rate. The parameter d represents an additional constant failure rate due to correctable but uncorrected failure modes. After the reliability growth process is terminated, the failure rate n(t)/t = c + d.

Harry W Jones↗

Vegetation Canopies and Objects of Arbitrary Shapes: Computer Generation and Bidirectional Reflectance Calculations

A general computer graphics based model is presented for computer generation of objects of arbitrary shape and for calculating Bidirectional Reflectance Factor (BRF) and scattering from them, in the optical region. The computer generation uses a modified Lindemayer system (L system) approach. For rendering on a computer screen, the object is divided into polygons, and innovative computer graphics techniques are used to display the object and to calculate the scattering and reflectance from the object. The use of the technique is illustrated with scattering from canopies of simulated corn plants and from a snow covered mountain. The scattering is quantified using measures like BRF and albedo and by rendering the objects with brightness of each of the two facets of a polygon proportional to the amount of light scattered from the object in the viewer's direction.

Goel, Narenda S.↗

A Comparison of Van Allen Belt Radiation Environment Modeling Programs: AE8/AP8 Legacy, AE9/AP9, and SPENVIS

In the space surrounding Earth there exists an active radiation environment consisting mostly of electrons and protons that have been trapped by Earths magnetic field. This radiation, also known as the Van Allen Belts, has the potential to damage man-made satellites in orbit; thus, proper precautions must be taken to shield NASA assets from this phenomenon. Data on the Van Allen Belts has been collected continuously by a multitude of space-based instruments since the beginning of space exploration. Subsequently, using theory to fill in the gaps in the collected data, computer models have been developed that take in the orbital information of a hypothetical mission and output the expected particle fluence and flux for that orbit. However, as new versions of the modeling system are released, users are left wondering how the new version differs from the old. Therefore, we performed a comparison of three different editions of the modeling system: AE8/AP8 (legacy), which is included in the model 9 graphical user interface as an option for ones calculations, AE9/AP9, and the Space Environment Information System (SPENVIS), which is an online-based form of AE8/AP8 developed by NASA and the European Space Agency that changed the code to allow the program to extrapolate data to predict fluence and flux at higher energies. Although this evaluation is still ongoing, it is predicted that the model 8 (legacy) and SPENVIS version will have identical outputs with the exception of the extended energy levels from SPENVIS, while model 9 will provide different fluences than model 8 based on additional magnetic field descriptions and on-orbit data.

Modeling Programs↗

Tropospheric Wind Observations with Doppler Lidars

Simpson Weather Associates has continued its efforts on the tools which operate the DLSM's s line-of-sight output products file. Due to the long model run times which were revealed in last month's benchmark tests, four model options for the LSM's atmospheric inputs are now included in the LSM. The user can choose to either spatially and/or temporally interpolate the inputs or use inputs closest to the DWL shot. A problem in the terrain assignment from the GADS was corrected. A database conversion tool was added to convert DWL line-of-sight ASCII files into database format for the graphic display models. Efforts have continued in simulating DWL horizontal wind components using the DAO ficcm Nature Run. Experiments 2 and 3 (40 days worth) were completed and sent to the DAO for their use in bracketing OSSE experiments. In addition, in order to investigate differences in the way regional (MM5) and global scale (ECMWF T213) models treat features such as clouds and subgrid scale variability, a gridded Mesoscale Atmospheric Data Set (MADS) was created and ready to be incorporated into simulation experiments.

Source record↗

Assessing electrogenetic activation via a network model of biological signal propagation

Introduction: Molecular communication is the transfer of information encoded by molecular structure and activity. We examine molecular communication within bacterial consortia as cells with diverse biosynthetic capabilities can be assembled for enhanced function. Their coordination, both in terms of engineered genetic circuits within individual cells as well as their population-scale functions, is needed to ensure robust performance. We have suggested that “electrogenetics,” the use of electronics to activate specific genetic circuits, is a means by which electronic devices can mediate molecular communication, ultimately enabling programmable control. Methods: Here, we have developed a graphical network model for dynamically assessing electronic and molecular signal propagation schemes wherein nodes represent individual cells, and their edges represent communication channels by which signaling molecules are transferred. We utilize graph properties such as edge dynamics and graph topology to interrogate the signaling dynamics of specific engineered bacterial consortia. Results: We were able to recapitulate previous experimental systems with our model. In addition, we found that networks with more distinct subpopulations (high network modularity) propagated signals more slowly than randomized networks, while strategic arrangement of subpopulations with respect to the inducer source (an electrode) can increase signal output and outperform otherwise homogeneous networks. Discussion: We developed this model to better understand our previous experimental results, but also to enable future designs wherein subpopulation composition, genetic circuits, and spatial configurations can be varied to tune performance. We suggest that this work may provide insight into the signaling which occurs in synthetically assembled systems as well as native microbial communities.

Chun, Kayla↗