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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Integrated Campaign Probabilistic Cost, Schedule, Performance, and Value for Program Office Support

This paper describes an integrated assessment tool developed at NASA Langley Research Center that incorporates probabilistic analysis of life cycle cost, schedule, launch performance, on-orbit performance, and value across a series of planned space-based missions, or campaign. Originally designed as an aid in planning the execution of missions to accomplish the National Research Council 2007 Earth Science Decadal Survey, it utilizes Monte Carlo simulation of a series of space missions for assessment of resource requirements and expected return on investment. Interactions between simulated missions are incorporated, such as competition for launch site manifest, to capture unexpected and non-linear system behaviors. A novel value model is utilized to provide an assessment of the probabilistic return on investment. A demonstration case is discussed to illustrate the tool utility.

Cornelius, David↗
NASA NTRS2012

Analytical Round Robin for Elastic-Plastic Analysis of Surface Cracked Plates: Phase I Results

An analytical round robin for the elastic-plastic analysis of surface cracks in flat plates was conducted with 15 participants. Experimental results from a surface crack tension test in 2219-T8 aluminum plate provided the basis for the inter-laboratory study (ILS). The study proceeded in a blind fashion given that the analysis methodology was not specified to the participants, and key experimental results were withheld. This approach allowed the ILS to serve as a current measure of the state of the art for elastic-plastic fracture mechanics analysis. The analytical results and the associated methodologies were collected for comparison, and sources of variability were studied and isolated. The results of the study revealed that the J-integral analysis methodology using the domain integral method is robust, providing reliable J-integral values without being overly sensitive to modeling details. General modeling choices such as analysis code, model size (mesh density), crack tip meshing, or boundary conditions, were not found to be sources of significant variability. For analyses controlled only by far-field boundary conditions, the greatest source of variability in the J-integral assessment is introduced through the constitutive model. This variability can be substantially reduced by using crack mouth opening displacements to anchor the assessment. Conclusions provide recommendations for analysis standardization.

Wells, D. N.↗
NASA NTRS2012

Plant Atrium System for Food Production in NASA's Deep Space Habitat Tests

In preparation for future human exploration missions to space, human habitat designs and concepts need to be tested to assess integration issues, power requirements, crew operations, and technology I subsystem performance. One potential subsystem for early habitats is supplemental food production. Fresh foods, such as vegetables and small fruits, could be harvested on a continuous basis to improve the diet and quality of life. The system would need to fit conveniently into the habitat and not interfere with other components or operations. To test this concept, a plant growing "atrium" was designed to surround the lift between the lower and upper modules of the Deep Space Habitat and deployed at NASA DRA TS test site in 2011 and at NASA's JSC in 20I2. With this approach, un-utilized volume provided an area for vegetable growth. For the 20 II test, mizuna, lettuce, basil, radish and sweetpotato plants were grown in trays using commercially available red I blue LED light fixtures. Seedlings were transplanted into the atrium and cared for by the crew. Plants were then harvested two weeks later following completion of the test. In 20I2, mizuna, lettuce, and radish plants were grown similarly but under flat panel banks of white LEDs. In 20 I2, the crew went through plant harvesting, including sanitizing the leafy greens and radishes, which were then consumed. Each test demonstrated successful production of vegetables within a functional hab module. The round red I blue LEDs for the 20Il test lighting cast a purple light in the hab, and were less uniformly distributed over the plant trays. The white LED panels provided broad spectrum light with more uniform distribution. Post-test questionnaires showed that the crew enjoyed tending and consuming the plants, and that the white LED light in 2012 provided welcome extra light for the main hab area.

Massa, Gioia↗
NASA NTRS2013

Plant Atrium System for Food Production in NASA's Deep Space Habitat Tests

In preparation for future human exploration missions to space, NASA evaluates habitat concepts to assess integration issues, power requirements, crew operations, technology, and system performance. The concept of a Food Production System utilizes fresh foods, such as vegetables and small fruits, harvested on a continuous basis, to improve the crew's diet and quality of life. The system would need to fit conveniently into the habitat and not interfere with other components or operations. To test this concept, a plant growing "atrium" was designed to surround the lift between the lower and upper modules of the Deep Space Habitat and deployed at NASA Desert Research and Technology Studies (DRATS) test site in 2011 and at NASA Johnson Space Center in 2012. With this approach, no-utilized volume provided an area for vegetable growth. For the 2011 test, mizuna, lettuce, basil, radish and sweetpotato plants were grown in trays using commercially available red I blue LED light fixtures. Seedlings were transplanted into the atrium and cared for by the. crew. Plants were then harvested two weeks later following completion of the test. In 2012, mizuna, lettuce, and radish plants were grown similarly but under flat panel banks of white LEDs. In 2012, the crew went through plant harvesting, including sanitizing tlie leafy greens and radishes, which were then consumed. Each test demonstrated successful production of vegetables within a functional hab module. The round red I blue LEDs for the 2011 test lighting cast a purple light in the hab, and were less uniformly distributed over the plant trays. The white LED panels provided broad spectrum light with more uniform distribution. Post-test questionnaires showed that the crew enjoyed tending and consuming the plants and that the white LED light in 2012 provided welcome extra light for the main HAB AREA.

Massa, Gioia D.↗
NASA NTRS2013

A Simple Model of Global Aerosol Indirect Effects

Most estimates of the global mean indirect effect of anthropogenic aerosol on the Earth's energy balance are from simulations by global models of the aerosol lifecycle coupled with global models of clouds and the hydrologic cycle. Extremely simple models have been developed for integrated assessment models, but lack the flexibility to distinguish between primary and secondary sources of aerosol. Here a simple but more physically based model expresses the aerosol indirect effect (AIE) using analytic representations of cloud and aerosol distributions and processes. Although the simple model is able to produce estimates of AIEs that are comparable to those from some global aerosol models using the same global mean aerosol properties, the estimates by the simple model are sensitive to preindustrial cloud condensation nuclei concentration, preindustrial accumulation mode radius, width of the accumulation mode, size of primary particles, cloud thickness, primary and secondary anthropogenic emissions, the fraction of the secondary anthropogenic emissions that accumulates on the coarse mode, the fraction of the secondary mass that forms new particles, and the sensitivity of liquid water path to droplet number concentration. Estimates of present-day AIEs as low as 5 W/sq m and as high as 0.3 W/sq m are obtained for plausible sets of parameter values. Estimates are surprisingly linear in emissions. The estimates depend on parameter values in ways that are consistent with results from detailed global aerosol-climate simulation models, which adds to understanding of the dependence on AIE uncertainty on uncertainty in parameter values.

Clouds↗
NASA NTRS2016

Air STAR Beyond Visual Range UAS Description and Preliminary Test Results

The NASA Airborne Subscale Transport Aircraft Research Unmanned Aerial System project's capabilities were expanded by updating the system design and concept of operations. The new remotely piloted airplane system design was flight tested to assess integrity and operational readiness of the design to perform flight research. The purpose of the system design is to improve aviation safety by providing a capability to validate, in high-risk conditions, technologies to prevent airplane loss of control. Two principal design requirements were to provide a high degree of reliability and that the new design provide a significant increase in test volume (relative to operations using the previous design). The motivation for increased test volume is to improve test efficiency and allow new test capabilities that were not possible with the previous design and concept of operations. Three successful test flights were conducted from runway 4-22 at NASA Goddard Space Flight Center's Wallops Flight Facility.

Cunningham, Kevin↗
NASA NTRS2018

Exploration Medical System Trade Study Tools Overview

ExMC is creating an ecosystem of tools to enable well-informed medical system trade studies. The suite of tools address important system implementation aspects of the space medical capabilities trade space and are being built using knowledge from the medical community regarding the unique aspects of space flight. Two integrating models, a systems engineering model and a medical risk analysis model, tie the tools together to produce an integrated assessment of the medical system and its ability to achieve medical system target requirements. This presentation will provide an overview of the various tools that are a part of the tool ecosystem. Initially, the presentation's focus will address the tools that supply the foundational information to the ecosystem. Specifically, the talk will describe how information that describes how medicine will be practiced is captured and categorized for efficient utilization in the tool suite. For example, the talk will include capturing what conditions will be planned for in-mission treatment, planned medical activities (e.g., periodic physical exam), required medical capabilities (e.g., provide imaging), and options to implement the capabilities (e.g., an ultrasound device). Database storage and configuration management will also be discussed. The presentation will include an overview of how these information tools will be tied to parameters in a Systems Modeling Language (SysML) model, allowing traceability to system behavioral, structural, and requirements content. The discussion will also describe an HRP-led enhanced risk assessment model developed to provide quantitative insight into each capability's contribution to mission success. Key outputs from these various tools, to be shared with the space medical and exploration mission development communities, will be assessments of medical system implementation option satisfaction of requirements and per-capability contributions toward achieving requirements.

Mindock, J.↗
NASA NTRS2020

Benefit Assessment of the Integrated Demand Management Concept for Multiple New York Metroplex Airports

Benefits of the Integrated Demand Management (IDM) concept were assessed utilizing a newly developed automated simulation capability called ‘Traffic Management Initiative Automated Simulation (TMIAutoSim).’ The IDM concept focuses on improving traffic flow management (TFM) by coordinating the FAA’s strategic Traffic Flow Management System (TFMS) with its more tactical Time-Based Flow Management (TBFM) system. The IDM concept leverages a new TFMS capability called Collaborative Trajectory Options Program (CTOP) to strategically pre-condition traffic demand flowing into a TBFM-managed arrival environment, where TBFM is responsible for tactically managing traffic by generating precise arrival schedules. The IDM concept was developed over a multi-year effort, focusing on solving New York metroplex airport arrival problems. TMIAutoSim closely mimics NASA’s high-fidelity simulation capabilities while enabling more data to be collected at higher speed. Using this new capability, the IDM concept was evaluated using realistic traffic across various weather scenarios. Six representative weather days were selected after clustering three months of historical data. For those selected six days, Newark Liberty International Airport (EWR) and LaGuardia Airport (LGA) arrival traffic scenarios were developed. For each selected day, the historical data were analyzed to accurately simulate actual operations and the weather impact of the day. The current day operations and the IDM concept operations were simulated for the same weather scenarios and the results were compared. The selected six days were categorized into two groups: ‘clear weather’ for days without Ground Delay Programs (GDP) and ‘convective weather’ for days with GDP and significant weather around New York metroplex airports. For the clear weather scenarios, IDM operations reduced last minute, unanticipated departure delays for short-haul flights within TBFM control boundaries with minimal to no impact on throughput and total delay. For the convective weather scenarios, IDM significantly reduced delays and increased throughput to the destination airports.

Traffic Management Initiative Automated Simulation↗
NASA NTRS2020

The GGCMI Phase 2 emulators: global gridded crop model responses to changes in CO2, temperature, water, and nitrogen (version 1.0)

Statistical emulation allows combining advantageous features of statistical and process-based crop models for understanding the effects of future climate changes on crop yields. We describe here the development of emulators for nine process-based crop models and five crops using output from the Global Gridded Model Intercomparison Project (GGCMI) Phase 2. The GGCMI Phase 2 experiment is designed with the explicit goal of producing a structured training dataset for emulator development that samples across four dimensions relevant to crop yields: atmospheric carbon dioxide (CO2) concentrations, temperature, water supply, and nitrogen inputs (CTWN). Simulations are run under two different adaptation assumptions: that growing seasons shorten in warmer climates, and that cultivar choice allows growing seasons to remain fixed. The dataset allows emulating the climatological-mean yield response of all models with a simple polynomial in mean growing-season values. Climatological-mean yields are a central metric in climate change impact analysis; we show here that they can be captured without relying on interannual variations. In general, emulation errors are negligible relative to differences across crop models or even across climate model scenarios; errors become significant only in some marginal lands where crops are not currently grown. We demonstrate that the resulting GGCMI emulators can reproduce yields under realistic future climate simulations, even though the GGCMI Phase 2 dataset is constructed with uniform CTWN offsets, suggesting that the effects of changes in temperature and precipitation distributions are small relative to those of changing means. The resulting emulators therefore capture relevant crop model responses in a lightweight, computationally tractable form, providing a tool that can facilitate model comparison, diagnosis of interacting factors affecting yields, and integrated assessment of climate impacts.

James A Franke↗
NASA NTRS2020

Apparent dust size discrepancy in aerosol reanalysis in north African dust after long-range transport

North African dust reaches the southeastern United States every summer. Size-resolved dust mass measurements taken in Miami, Florida, indicate that more than one-half of the surface dust mass concentrations reside in particles with geometric diameters less than 2.1 µm, while vertical profiles of micropulse lidar depolarization ratios show dust reaching above 4 km during pronounced events. These observations are compared to the representation of dust in the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) aerosol reanalysis and closely related Goddard Earth Observing System model version 5 (GEOS-5) Forward Processing (FP) aerosol product, both of which assimilate satellite-derived aerosol optical depths using a similar protocol and inputs. These capture the day-to-day variability in aerosol optical depth well, in a comparison to an independent sun-photometer-derived aerosol optical depth dataset. Most of the modeled dust mass resides in diameters between 2 and 6 µm, in contrast to the measurements. Model-specified mass extinction efficiencies equate light extinction with approximately 3 times as much aerosol mass, in this size range, compared to the measured dust sizes. GEOS-5 FP surface-layer sea salt mass concentrations greatly exceed observed values, despite realistic winds and relative humidities. In combination, these observations help explain why, despite realistic total aerosol optical depths, (1) free-tropospheric model volume extinction coefficients are lower than those retrieved from the micro-pulse lidar, suggesting too-low model dust loadings in the free troposphere, and (2) model dust mass concentrations near the surface can be higher than those measured. The modeled vertical distribution of dust, when captured, is reasonable. Large, aspherical particles exceeding the modeled dust sizes are also occasionally present, but dust particles with diameters exceeding 10 µm contribute little to the measured total dust mass concentrations after such long-range transport. Remaining uncertainties warrant a further integrated assessment to confirm this study's interpretations.

MEERA-2 aerosols reanalysis↗
NASA NTRS2020

Harmonization of global land use change and management for the period 850–2100 (LUH2) for CMIP6

Human land use activities have resulted in large changes to the biogeochemical and biophysical properties of the Earth's surface, with consequences for climate and other ecosystem services. In the future, land use activities are likely to expand and/or intensify further to meet growing demands for food, fiber, and energy. As part of the World Climate Research Program Coupled Model Intercomparison Project (CMIP6), the international community has developed the next generation of advanced Earth system models (ESMs) to estimate the combined effects of human activities (e.g., land use and fossil fuel emissions) on the carbon–climate system. A new set of historical data based on the History of the Global Environment database (HYDE), and multiple alternative scenarios of the future (2015–2100) from Integrated Assessment Model (IAM) teams, is required as input for these models. With most ESM simulations for CMIP6 now completed, it is important to document the land use patterns used by those simulations. Here we present results from the Land-Use Harmonization 2 (LUH2) project, which smoothly connects updated historical reconstructions of land use with eight new future projections in the format required for ESMs. The harmonization strategy estimates the fractional land use patterns, underlying land use transitions, key agricultural management information, and resulting secondary lands annually, while minimizing the differences between the end of the historical reconstruction and IAM initial conditions and preserving changes depicted by the IAMs in the future. The new approach builds on a similar effort from CMIP5 and is now provided at higher resolution (0.25°×0.25°) over a longer time domain (850–2100, with extensions to 2300) with more detail (including multiple crop and pasture types and associated management practices) using more input datasets (including Landsat remote sensing data) and updated algorithms (wood harvest and shifting cultivation); it is assessed via a new diagnostic package. The new LUH2 products contain > 50 times the information content of the datasets used in CMIP5 and are designed to enable new and improved estimates of the combined effects of land use on the global carbon–climate system.

land use land cover change↗
NASA NTRS2021

A permafrost implementation in the simple carbon-climate model Hector v.2.3.pf

Permafrost currently stores more than a fourth of global soil carbon. A warming climate makes this carbon increasingly vulnerable to decomposition and release into the atmosphere in the form of greenhouse gases. The resulting climate feedback can be estimated using land surface models, but the high complexity and computational cost of these models make it challenging to use them for estimating uncertainty, exploring novel scenarios, and coupling with other models. We have added a representation of permafrost to the simple, open-source global carbon–climate model Hector, calibrated to be consistent with both historical data and 21st century Earth system model projections of permafrost thaw. We include permafrost as a separate land carbon pool that becomes available for decomposition into both methane (CH4) and carbon dioxide (CO2) once thawed; the thaw rate is controlled by region-specific air temperature increases from a preindustrial baseline. We found that by 2100 thawed permafrost carbon emissions increased Hector’s atmospheric CO2 concentration by 5 %–7 % and the atmospheric CH4 concentration by 7 %–12 %, depending on the future scenario, resulting in 0.2–0.25 ∘C of additional warming over the 21st century. The fraction of thawed permafrost carbon available for decomposition was the most significant parameter controlling the end-of-century temperature change in the model, explaining around 70 % of the temperature variance, and was distantly followed by the initial stock of permafrost carbon, which contributed to about 10 % of the temperature variance. The addition of permafrost in Hector provides a basis for the exploration of a suite of science questions, as Hector can be cheaply run over a wide range of parameter values to explore uncertainty and can be easily coupled with integrated assessment and other human system models to explore the economic consequences of warming from this feedback.

Dawn L. Woodard↗
NASA NTRS1991

An experimental study of wall adaptation and interference assessment using Cauchy integral formula

This paper summarizes the results of an experimental study of combined wall adaptation and residual interference assessment using the Cauchy integral formula. The experiments were conducted on a supercritical airfoil model in the Langley 0.3-m Transonic Cryogenic Tunnel solid flexible wall test section. The ratio of model chord to test section height was about 0.7. The method worked satisfactorily in reducing the blockage interference and demonstrated the primary requirement for correcting for the blockage effects at high model incidences to correctly determine high lift characteristics. The studies show that the method has potential for reducing the residual interference to considerably low levels. However, corrections to blockage and upwash velocities gradients may still be required for the final adapted wall shapes.

Murthy, A. V.↗
NASA NTRS1975

Evaluation of Oak Ridge National Laboratory report on Technology Assessment of Modular Integrated Utility Systems (MIUS)

The evaluation indicates the need to establish professional standards for judging the adequacy with which assessments are performed and for analyzing the sufficiency of the definition of task-objectives that are given to or posited by assessment entities. Three basic performance criteria are posited: interpretability, warrantability, and serviceability of utility of assessment outcome to the relevant decisional entity or entities.

Maxo, L. H.↗
NASA NTRS2015

Perspectives on Climate Effects on Agriculture: The International Efforts of AgMIP in Sub-Saharan Africa

Agriculture in Sub-Saharan Africa (SSA) is experiencing climate change-related effects that call for integrated regional assessments, yet capacity for these assessments has been low. The Agricultural Model Intercomparison and Improvement Project (AgMIP) is advancing research on integrated regional assessments of climate change that include climate, crop, and economic modeling and analysis. Through AgMIP, regional integrated assessments are increasingly gaining momentum in SSA, and multi-institutional regional research teams (RRTs) centered in East, West, and Southern· Africa are generating new information on climate change impacts and adaptation in selected agricultural systems. The research in Africa is organized into four RRTs and a coordination team. Each of the RRTs in SSA is composed of scientists from the Consultative Group of International Agricultural Research (CGIAR) institutions, National Agriculture Research institutes (NARs), and universities consisting of experts in crop and economic modeling, climate, and information technology. Stakeholder involvement to inform specific agricultural systems to be evaluated, key outputs, and the representative agricultural pathways (RAPs), is undertaken at two levels: regional and national, in order to contribute to decision making at these levels. Capacity building for integrated assessment (lA) is a key component that is undertaken continuously through interaction with experts in regional and SSA-wide workshops, and through joint creation of tools. Many students and research affiliates have been identified and entrained as part of capacity building in IA. Bi-monthly updates on scholarly publications in climate change in Africa also serve as a vehicle for knowledge-sharing. With 60 scientists already trained and actively engaged in IA and over 80 getting monthly briefs on the latest information on climate change, a climate-informed community of experts is gradually taking shape in SSA. (See Part 2, Appendices 3-5 in this volume for AgMIP Regional Workshop reports.)

Kihara, Job↗
NASA NTRS2000

Integrated Testing Regimen: Assessment of Countermeasures for Long Duration Space Flight

Space flight has been shown to induce changes in the physiology of crewmembers which can adversely affect their performance. The objectives of Countermeasures Evaluation and Validation Project (CEVP) are to develop and validate potential countermeasures to the deleterious effects of space flight for operational implementation and use. In order to accomplish this objective, a group of standardized tests, the Integrated Testing Regimen or ITR, will be utilized for the evaluation of candidate countermeasures. Additionally, the ITR will illuminate intersystem effects of the potential countermeasures and provide normative values for the physiological responses. Due to the small number of crewmembers available as test subjects, statistically rigorous validation of countermeasures presents a challenging problem. Strategies for reliable evaluation of small N clinical studies will be utilized for these activities. These approaches will permit effective analysis of promising countermeasure to support human space flights of increasing duration.

Sams, Clarence F.↗
NASA NTRS2006

A Strategy to Integrate Probabilistic Risk Assessment into Design and Development Processes for Aerospace Based pon Mars Exploration Rover Experiences

This paper will discuss the Probabilistic Risk Assessment (PRA) effort and its involvement with related activities during the development of the Mars Exploration Rover (MER). The Rovers were launched 2003.June.10 (Spirit) and 2003.July.7 (Opportunity), and both have proven very successful. Although designed for a 90-day mission, the Rovers have been operating for over two earth years. This paper will review aspects of how the MER project integrated PRA into the design and development process. A companion paper (Development of the Mars Exploration Rover PRA) will describe the MER PRA and design changes from those results.

Probabilistic Risk Assessment (PRA)↗
NASA NTRS2024

Soil Salinity Level Assessment and Prediction Integrating UAV-borne Hyperspectral Imaging and Machine Learning Algorithms to Combat Desertification

In response to the ongoing global food crisis, the United Nations has identified “Zero Hunger” as one of its Sustainable Development Goals. A central contributor to the crisis is the process in which agricultural lands go through desertification. Research has shown a direct correlation between soil salinity and desertification - increased salinity levels indicate a higher risk for desertification. Furthermore, researchers have explored various techniques to map soil salinity, but these methods are oftentimes inefficient and don’t address future salinity predictions. To improve desertification monitoring, soil salinity can be observed via hyperspectral imaging on unmanned aerial vehicles (UAVs) to predict the risk of agricultural desertification using artificial intelligence (AI) and machine learning (ML) techniques. A significant gap exists in past research that applies ML and imaging techniques to soil salinity: convolutional neural networks (CNNs) and regression models are rarely leveraged together, despite the efficiency and accuracy of these models. To compensate for this gap, the proposed system leverages the use of these AI and ML models to improve soil assessment and prediction techniques. This approach involves three steps - data collection, image analysis, and future prediction. Using hyperspectral cameras on UAVs to collect the data from the region, a trained CNN model will output estimated soil salinity levels at a specific time. The estimations will then be analyzed by a regression model to assess the accuracy of future soil salinity predictions. The proposed system will identify regions at risk of desertification to help farmers mitigate agricultural loss, in turn helping alleviate the food crisis.

UAV systems↗