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At least 613 records · Page 34

orbitize! v3: Orbit fitting for the High-contrast Imaging Community

orbitize! is a package for Bayesian modeling of the orbital parameters of resolved binary objects from time series measurements. It was developed with the needs of the high-contrast imaging community in mind, and has since also become widely used in the binary star community. A generic orbitize! use case involves translating relative astrometric time series, optionally combined with radial velocity or astrometric time series, into a set of derived orbital posteriors. This paper is published alongside the release of orbitize! version 3.0, which has seen significant enhancements in functionality and accessibility since the release of version 1.0 (Blunt et al., 2020).

Sarah Blunt↗

Software Engineering Tools for Scientific Models

Software tools were constructed to address issues the NASA Fortran development community faces, and they were tested on real models currently in use at NASA. These proof-of-concept tools address the High-End Computing Program and the Modeling, Analysis, and Prediction Program. Two examples are the NASA Goddard Earth Observing System Model, Version 5 (GEOS-5) atmospheric model in Cell Fortran on the Cell Broadband Engine, and the Goddard Institute for Space Studies (GISS) coupled atmosphere- ocean model called ModelE, written in fixed format Fortran.

Abrams, Marc↗

Getting a Cohesive Answer from a Common Start: Scalable Multidisciplinary Analysis through Transformation of a Systems Model

One of the challenges of systems engineering is in working multidisciplinary problems in a cohesive manner. When planning analysis of these problems, system engineers must trade between time and cost for analysis quality and quantity. The quality often correlates with greater run time in multidisciplinary models and the quantity is associated with the number of alternatives that can be analyzed. The trade-off is due to the resource intensive process of creating a cohesive multidisciplinary systems model and analysis. Furthermore, reuse or extension of the models used in one stage of a product life cycle for another is a major challenge. Recent developments have enabled a much less resource-intensive and more rigorous approach than hand-written translation scripts between multi-disciplinary models and their analyses. The key is to work from a core systems model defined in a MOF-based language such as SysML and in leveraging the emerging tool ecosystem, such as Query/View/Transformation (QVT), from the OMG community. SysML was designed to model multidisciplinary systems. The QVT standard was designed to transform SysML models into other models, including those leveraged by engineering analyses. The Europa Habitability Mission (EHM) team has begun to exploit these capabilities. In one case, a Matlab/Simulink model is generated on the fly from a system description for power analysis written in SysML. In a more general case, symbolic analysis (supported by Wolfram Mathematica) is coordinated by data objects transformed from the systems model, enabling extremely flexible and powerful design exploration and analytical investigations of expected system performance.

Operational QVT↗

Unifying radiative transfer models in computer graphics and remote sensing, Part I: A Survey

The constellation of Earth-observing satellites continuously collects measurements of scattered radiance, which must be transformed into geophysical parameters in order to answer fundamental scientific questions about the Earth. Retrieval of these parameters requires highly flexible, accurate, and fast forward and inverse radiative transfer models. Existing forward models used by the remote sensing community are typically accurate and fast, but sacrifice flexibility by assuming the atmosphere or ocean is composed of plane-parallel layers. Monte Carlo forward models can handle more complex scenarios such as 3D spatial heterogeneity, but are relatively slower. We propose looking to the computer graphics community for inspiration to improve the statistical efficiency of Monte Carlo forward models and explore new approaches to inverse models for remote sensing. In Part 1 of this work, we examine the evolution of radiative transfer models in computer graphics and highlight recent advancements that have the potential to push forward models in remote sensing beyond their current periphery of realism.

Radiative transfer↗

The use of airborne and ground-based measurements of launch vehicle HCl puffs in a finite difference parameter estimation procedure

Model 4 of the multilayer diffusion models, version 5 (MDMV5) is discussed. MDMV5 is designed to help factor considerations of the potential environment impact of a given launch operation into the actual launch decision process. The model supports this decision process by providing quantitative estimates of particular air quality indices at a set of spatial positions in the launch area and surrounding communities, for specified meteorological conditions. Modeling concepts, the finite difference estimation algorithm, and data application and results are examined.

Englar, T. S., Jr.↗

NASA Integrated Model Centric Architecture (NIMA) Model Use and Re-Use

This whitepaper accepts the goals, needs and objectives of NASA's Integrated Model-centric Architecture (NIMA); adds experience and expertise from the Constellation program as well as NASA's architecture development efforts; and provides suggested concepts, practices and norms that nurture and enable model use and re-use across programs, projects and other complex endeavors. Key components include the ability to effectively move relevant information through a large community, process patterns that support model reuse and the identification of the necessary meta-information (ex. history, credibility, and provenance) to safely use and re-use that information. In order to successfully Use and Re-Use Models and Simulations we must define and meet key organizational and structural needs: 1. We must understand and acknowledge all the roles and players involved from the initial need identification through to the final product, as well as how they change across the lifecycle. 2. We must create the necessary structural elements to store and share NIMA-enabled information throughout the Program or Project lifecycle. 3. We must create the necessary organizational processes to stand up and execute a NIMA-enabled Program or Project throughout its lifecycle. NASA must meet all three of these needs to successfully use and re-use models. The ability to Reuse Models a key component of NIMA and the capabilities inherent in NIMA are key to accomplishing NASA's space exploration goals. 11

Conroy, Mike↗

Chimeric Mouse Models for Space Radiation Risk Investigations

Assessment of human health risks associated with space radiation exposure is based largely on the knowledge learned from studies in which animals, mostly rodents, are exposed to high-LET radiation on the ground. It has been recognized that translation of animal results to meaningful implications for human disease can be challenging, particularly for certain risk categories such as the high-LET radiation effects in the central nervous system (CNS). Considering limitations in utilizing non-human primates and clinical studies in humans, chimeric animals can potentially bridge the knowledge gap between rodents and humans. In a chimeric animal, a specific organ or a cell type is replaced with respective human cells that are functional. A number of chimeric mouse models have been developed in the medical research community to study human diseases, and some of the models can potentially be used for NASA applications. For instance, mice engrafted with human hepatocytes, which have been used in studies of genotoxicity from carcinogen exposures, can be used for quantification of space radiation damage. A chimeric brain model, which was shown to perform superiorly in memory and cognitive tests, can also be a candidate for studying the CNS effects of radiation. It has also been reported that mice engrafted with human hematopoietic progenitor cells were exposed to X-rays and high-LET Si ions to investigate the radiation effects in the immune system. In a pilot study, we use PXB mice whose livers contain >90% human cells. These mice are exposed to gamma rays for investigations of DNA damage and transcriptomics changes in the humanized livers. Results obtained from PXB mice will be compared non-engrafted control animals from the same background strain that are exposed to identical conditions. The aim of the study is to determine whether chimeric mouse models are suitable for investigations of space radiation risks.

Honglu Wu↗

Chimeric Mouse Models for Space Radiation Risk Investigations

Assessment of human health risks associated with space radiation exposure is based largely on the knowledge learned from studies in which animals, mostly rodents, are exposed to high-LET radiation on the ground. It has been recognized that translation of animal results to meaningful implications for human disease can be challenging, particularly for certain risk categories such as the high-LET radiation effects in the central nervous system (CNS). Considering limitations in utilizing non-human primates and clinical studies in humans, chimeric animals can potentially bridge the knowledge gap between rodents and humans. In a chimeric animal, a specific organ or a cell type is replaced with respective human cells that are functional. A number of chimeric mouse models have been developed in the medical research community to study human diseases, and some of the models can potentially be used for NASA applications. For instance, mice engrafted with human hepatocytes, which have been used in studies of genotoxicity from carcinogen exposures, can be used for quantification of space radiation damage. A chimeric brain model, which was shown to perform superiorly in memory and cognitive tests, can also be a candidate for studying the CNS effects of radiation. It has also been reported that mice engrafted with human hematopoietic progenitor cells were exposed to X-rays and high-LET Si ions to investigate the radiation effects in the immune system. In a pilot study, we use PXB mice whose livers contain >90% human cells. These mice are exposed to gamma rays for investigations of DNA damage and transcriptomics changes in the humanized livers. Results obtained from PXB mice will be compared non-engrafted control animals from the same background strain that are exposed to identical conditions. The aim of the study is to determine whether chimeric mouse models are suitable for investigations of space radiation risks.

Honglu Wu↗

Chimeric Mouse Models for Space Radiation Risk Investigations

Assessment of human health risks associated with space radiation exposure is based largely on the knowledge learned from studies in which animals, mostly rodents, are exposed to high-LET radiation on the ground. It has been recognized that translation of animal results to meaningful implications for human disease can be challenging, particularly for certain risk categories such as the high-LET radiation effects in the central nervous system (CNS). Considering limitations in utilizing non-human primates and clinical studies in humans, chimeric animals can potentially bridge the knowledge gap between rodents and humans. In a chimeric animal, a specific organ or a cell type is replaced with respective human cells that are functional. A number of chimeric mouse models have been developed in the medical research community to study human diseases, and some of the models can potentially be used for NASA applications. Here we investigate use of mice engrafted with human hepatocytes, which have been used in studies of genotoxicity from carcinogen exposures, for assessment of space radiation damage. In a pilot study, we use PXB mice whose livers contain >90% human cells and have been found to function nearly identically to human liver tissues. These mice were exposed to gamma rays for investigations of DNA damage, transcriptomics, and histopathological changes in the humanized livers. Results obtained from PXB mice were compared non-engrafted control animals from the same background strain that are exposed to identical conditions. Preliminary data from histopathological analysis suggest chimeric mouse models are suitable for investigations of space radiation risks, as the humanized liver tissue exhibited changes induced by radiation and was markedly distinct from the liver tissue from the control animals (Fox Chase SCID mice).

Radiation effects↗

Chimeric Mouse Models for Space Radiation Risk Investigations

Assessment of human health risks associated with space radiation exposure is based largely on the knowledge learned from studies in which animals, mostly rodents, are exposed to high-LET radiation on the ground. It has been recognized that translation of animal results to meaningful implications for human disease can be challenging, particularly for certain risk categories such as the high-LET radiation effects in the central nervous system (CNS). Considering limitations in utilizing non-human primates and clinical studies in humans, chimeric animals can potentially bridge the knowledge gap between rodents and humans. In a chimeric animal, a specific organ or a cell type is replaced with respective human cells that are functional. A number of chimeric mouse models have been developed in the medical research community to study human diseases, and some of the models can potentially be used for NASA applications. Here we investigate use of mice engrafted with human hepatocytes, which have been used in studies of genotoxicity from carcinogen exposures, for assessment of space radiation damage. In a pilot study, we use PXB mice whose livers contain >90% human cells and have been found to function nearly identically to human liver tissues. These mice were exposed to gamma rays for investigations of DNA damage, transcriptomics, and histopathological changes in the humanized livers. Results obtained from PXB mice were compared non-engrafted control animals from the same background strain that are exposed to identical conditions. Preliminary data from histopathological analysis suggest chimeric mouse models are suitable for investigations of space radiation risks, as the humanized liver tissue exhibited changes induced by radiation and was markedly distinct from the liver tissue from the control animals (Fox Chase SCID mice).

Radiation effects↗

Getting a Cohesive Answer from a Common Start: Scalable Multidisciplinary Analysis through Transformation of a System Model

One of the challenges of systems engineering is in working multidisciplinary problems in a cohesive manner. When planning analysis of these problems, system engineers must tradeoff time and cost for analysis quality and quantity. The quality is associated with the fidelity of the multidisciplinary models and the quantity is associated with the design space that can be analyzed. The tradeoff is due to the resource intensive process of creating a cohesive multidisciplinary system model and analysis. Furthermore, reuse or extension of the models used in one stage of a product life cycle for another is a major challenge. Recent developments have enabled a much less resource-intensive and more rigorous approach than handwritten translation scripts or codes of multidisciplinary models and their analyses. The key is to work from a core system model defined in a MOF-based language such as SysML and in leveraging the emerging tool ecosystem, such as Query-View- Transform (QVT), from the OMG community. SysML was designed to model multidisciplinary systems and analyses. The QVT standard was designed to transform SysML models. The Europa Hability Mission (EHM) team has begun to exploit these capabilities. In one case, a Matlab/Simulink model is generated on the fly from a system description for power analysis written in SysML. In a more general case, a symbolic mathematical framework (supported by Wolfram Mathematica) is coordinated by data objects transformed from the system model, enabling extremely flexible and powerful tradespace exploration and analytical investigations of expected system performance.

Cole, Bjorn↗

Examining the Link Between Food Prices and Food Insecurity: a Multi-Level Analysis of Maize Price and Birthweight in Kenya

In developing countries where many poor people rely on rainfed, locally produced food for the majority of their caloric intake, shifts in climate and weather patterns can dramatically reduce agricultural productivity. The reduction in agricultural productivity reduces overall food availability and ultimately impacts food accessibility, putting millions of people at risk for malnutrition. In this project we focus on Kenya where roughly a third of households are food insecure. We examine the relationship of the price of maize and low birth weight to help quantify the impact of local food prices on one outcome of household food insecurity. Using spatially referenced data from recent Kenyan Demographic and Health Survey datasets, price data, livelihood information, and a remotely sensed-based measure of local growing season productivity, we develop a dataset linking pregnancies occurring from 2001 to 2008 to the spatially and temporally relevant maize price data. We construct several regression models to examine the impact of local maize prices and remotely sensed based estimates of crop production on infant birth weight - specifically low birth weight. The results of the models highlight the importance of including community crop production to evaluate maize price impacts on low birth weight outcomes. Also, because of the positive correlation between pre-pregnancy maize prices and birth weight, the results suggest that some households may benefit from high prices or that high prices may impact the number of conceptions. More generally, our work demonstrates that multilevel models that account for community-level variation are important for disentangling these complex relationships and can contribute to the discussion of how to design more effective food policies.

Low birth weight↗

Reinforced Carbon-Carbon Subcomponent Flat Plate Impact Testing for Space Shuttle Orbiter Return to Flight

Following the tragedy of the Space Shuttle Columbia on February 1, 2003, a major effort commenced to develop a better understanding of debris impacts and their effect on the Space Shuttle subsystems. An initiative to develop and validate physics-based computer models to predict damage from such impacts was a fundamental component of this effort. To develop the models it was necessary to physically characterize Reinforced Carbon-Carbon (RCC) and various debris materials which could potentially shed on ascent and impact the Orbiter RCC leading edges. The validated models enabled the launch system community to use the impact analysis software LS DYNA to predict damage by potential and actual impact events on the Orbiter leading edge and nose cap thermal protection systems. Validation of the material models was done through a three-level approach: fundamental tests to obtain independent static and dynamic material model properties of materials of interest, sub-component impact tests to provide highly controlled impact test data for the correlation and validation of the models, and full-scale impact tests to establish the final level of confidence for the analysis methodology. This paper discusses the second level subcomponent test program in detail and its application to the LS DYNA model validation process. The level two testing consisted of over one hundred impact tests in the NASA Glenn Research Center Ballistic Impact Lab on 6 by 6 in. and 6 by 12 in. flat plates of RCC and evaluated three types of debris projectiles: BX 265 External Tank foam, ice, and PDL 1034 External Tank foam. These impact tests helped determine the level of damage generated in the RCC flat plates by each projectile. The information obtained from this testing validated the LS DYNA damage prediction models and provided a certain level of confidence to begin performing analysis for full-size RCC test articles for returning NASA to flight with STS 114 and beyond.

Melis, Matthew E.↗

Joint Composable Object Model and LVC Methodology

Within the Department of Defense, multiple architectures are created to serve and fulfill one or several specific service or mission related LVC training goals. Multiple Object Models exist across and within those architectures and it is there that those disparate object models are a major source of interoperability problems when developing and constructing the training scenarios. The two most commonly used architectures are; HLA and TENA, with DIS and CTIA following close behind in terms of the number of users. Although these multiple architectures can share and exchange data the underlying meta-models for runtime data exchange are quite different, requiring gateways/translators to bridge between the different object model representations; while the Department of Defense's use of gateways are generally effective in performing these functions, as the LVC environment increases so too does the cost and complexity of these gateways. Coupled with the wide range of different object models across the various user communities we increase the propensity for run time errors, increased programmer stop gap measures during coordinated exercises, or failure of the system as a whole due to unknown or unforeseen incompatibilities. The Joint Composable Object Model (JCOM) project was established under an M&S Steering Committee (MSSC)-sponsored effort with oversight and control placed under the Joint Forces Command J7 Advanced Concepts Program Directorate. The purpose of this paper is to address the initial and the current progress that has been made in the following areas; the Conceptual Model Development Format, the Common Object Model, the Architecture Neutral Data Exchange Model (ANDEM), and the association methodology to allow the re-use of multiple architecture object models and the development of the prototype persistent reusable library.

Rheinsmith, Richard↗

Implementing a Nitrogen-Based Model for Autotrophic Respiration Using Satellite and Field Observations

The rate of carbon accumulation by terrestrial plant communities in a process-level, mechanistic modeling is the difference of the rate of gross photosynthesis by a canopy (A(sub g)) and autotrophic respiration (R) of the stand. Observations for different biomes often show that R to be a large and variable fraction of A(sub g), ca. 35% to 75%, although other studies suggest the ratio of R and A(sub g) to be less variable. Here, R has been calculated according to the two compartment model as being the sum of maintenance and growth components. The maintenance respiration of foliage and living fine roots for different biomes has been determined objectively from observed nitrogen content of these organs. The sapwood maintenance respiration is based on pipe theory, and checked against an independently derived equation considering sapwood biomass and its maintenance coefficient. The growth respiration has been calculated from the difference of A(sub g) and maintenance respiration. The A(sub g) is obtained as the product of biome-specific radiation use efficiency for gross photosynthesis under unstressed conditions and intercepted photosynthetically active radiation, and adjusted for stress. Calculations have been done using satellite and ground observations for 36 consecutive months (1987-1989) over large contiguous areas (ca. 10(exp 5) sq km) of boreal forests, crop land, temperate deciduous forest, temperate grassland, tropical deciduous forest, tropical evergreen forest, tropical savanna, and tundra. The ratio of annual respiration and gross photosynthesis, (R/A(sub g)), is found to be 0.5-0.6 for temperate and cold adopted biome areas, but somewhat higher for tropical biome areas (0.6-0.7). Interannual variation of the fluxes is found to be generally less than 15%. Calculated fluxes are compared with observations and several previous estimates. Results of sensitivity analysis are presented for uncertainties in parameterization and input data. It is found that uncertainty in determining maintenance respiration for tropical biomes is such that R/A(sub g) for these biomes could be similar to that for temperate biomes.

Choudhury, Bhaskar J.↗

Pliocene Model Intercomparison Project Phase 3 (PlioMIP3) – Science Plan and Experimental Design

The Pliocene Model Intercomparison Project (PlioMIP) was initiated in 2008. Over two phases PlioMIP has helped co-ordinate the experimental design and publication strategy of the community, which has included an increasing number of climate models and modelling groups from around the world. It has engaged with palaeoenvironmental scientists to foster new data synthesis supporting the construction of new model boundary conditions, as well as to facilitate new data-model comparisons. The work has advanced our understanding of Pliocene climates and environments, enhanced our knowledge regarding the ability of complex climate and Earth System models to accurately simulate climate change, and helped to refine our estimates of how sensitive the climate system is to forcing conditions. In this community protocol paper, we outline the scientific plan for PlioMIP Phase 3 (PlioMIP3). This plan provides the required guidance to participating modelling groups from around the world to successfully set up and perform PlioMIP3 climate model experiments. The project is open to new participants from the scientific community (both from the climate modelling and geosciences communities). In PlioMIP3, we retain the PlioMIP2 Core experiments (Eoi 400 , E 280 ) and extend the Core requirements to include either an experiment focussed on the Early Pliocene or an alternative Late Pliocene simulation (or both). These additions (a) allow a comparison of Early and Late Pliocene warm intervals and help build research connections and synergy with the MioMIP (Miocene Model Intercomparison Project - also known as DeepMIP-Miocene) and PlioMioVAR projects (Pliocene-Miocene Variability Working Group), and (b) create an alternative time slice simulation for 3.205 Ma (MIS KM5c) through removal of some of the largest palaeogeographic differences introduced between PlioMIP1 and 2 resulting in minimal land-sea mask variations from the modern. In addition, we present ten optional experiments designed to enhance our assessment of climate sensitivity and to explore the uncertainty in greenhouse gas-related forcing. For the first time, we introduce orbital sensitivity experiments into the science plan, as well as simulations incorporating dynamic vegetation-climate feedbacks and an experiment designed to examine the potential significance of East Antarctic Ice Sheet boundary condition uncertainty. These changes enhance palaeo-to-future scientific connections and enable an exploration of the significance of palaeogeographic uncertainties on climate simulations.

Climate modelling↗

Bridging the Engineering and Medicine Gap

A primary challenge NASA faces is communication between the disparate entities of engineers and human system experts in life sciences. Clear communication is critical for exploration mission success from the perspective of both risk analysis and data handling. The engineering community uses probabilistic risk assessment (PRA) models to inform their own risk analysis and has extensive experience managing mission data, but does not always fully consider human systems integration (HSI). The medical community, as a part of HSI, has been working 1) to develop a suite of tools to express medical risk in quantitative terms that are relatable to the engineering approaches commonly in use, and 2) to manage and integrate HSI data with engineering data. This talk will review the development of the Integrated Medical Model as an early attempt to bridge the communication gap between the medical and engineering communities in the language of PRA. This will also address data communication between the two entities in the context of data management considerations of the Medical Data Architecture. Lessons learned from these processes will help identify important elements to consider in future communication and integration of these two groups.

Walton, M.↗

Impact Testing on Reinforced Carbon-Carbon Flat Panels with Ice Projectiles for the Space Shuttle Return to Flight Program

Following the tragedy of the Orbiter Columbia (STS-107) on February 1, 2003, a major effort commenced to develop a better understanding of debris impacts and their effect on the space shuttle subsystems. An initiative to develop and validate physics-based computer models to predict damage from such impacts was a fundamental component of this effort. To develop the models it was necessary to physically characterize reinforced carbon-carbon (RCC) along with ice and foam debris materials, which could shed on ascent and impact the orbiter RCC leading edges. The validated models enabled the launch system community to use the impact analysis software LS-DYNA (Livermore Software Technology Corp.) to predict damage by potential and actual impact events on the orbiter leading edge and nose cap thermal protection systems. Validation of the material models was done through a three-level approach: Level 1--fundamental tests to obtain independent static and dynamic constitutive model properties of materials of interest, Level 2--subcomponent impact tests to provide highly controlled impact test data for the correlation and validation of the models, and Level 3--full-scale orbiter leading-edge impact tests to establish the final level of confidence for the analysis methodology. This report discusses the Level 2 test program conducted in the NASA Glenn Research Center (GRC) Ballistic Impact Laboratory with ice projectile impact tests on flat RCC panels, and presents the data observed. The Level 2 testing consisted of 54 impact tests in the NASA GRC Ballistic Impact Laboratory on 6- by 6-in. and 6- by 12-in. flat plates of RCC and evaluated three types of debris projectiles: Single-crystal, polycrystal, and "soft" ice. These impact tests helped determine the level of damage generated in the RCC flat plates by each projectile and validated the use of the ice and RCC models for use in LS-DYNA.

Melis, Matthew E.↗