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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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NASA NTRS2012

Aquarius: The Instrument and Initial Results

Aquarius was launched on June 10, 2011 aboard the Aquarius/SAC-D observatory and the instrument has been operating continuously since the initial turned-on was completed on August 25. The initial observed antenna temperatures were close to predicted and the first salinity map was released in September. In order to map the ocean salinity field, Aquarius includes several special features such as the inclusion of a scatterometer to provide a roughness correction, measurement of the third Stokes parameter to correct for Faraday rotation, and fast sampling to mitigate the effects of RFI. This paper provides an overview of the instrument and an example of initial results. Details are covered in subsequent papers in the session on Aquarius

Ocean salinity↗
NASA NTRS2014

Toward Improved Land Surface Initialization in Support of Regional WRF Forecasts at the Kenya Meteorological Service (KMS)

SPoRT/SERVIR/RCMRD/KMS Collaboration: Builds off strengths of each organization. SPoRT: Transition of satellite, modeling and verification capabilities; SERVIR‐Africa/RCMRD: International capacity-building expertise; KMS: Operational organization with regional weather forecasting expertise in East Africa. Hypothesis: Improved land‐surface initialization over Eastern Africa can lead to better temperature, moisture, and ultimately precipitation forecasts in NWP models. KMS currently initializes Weather Research and Forecasting (WRF) model with NCEP/Global Forecast System (GFS) model 0.5‐deg initial / boundary condition data. LIS will provide much higher‐resolution land‐surface data at a scale more representative to regional WRF configuration. Future implementation of real‐time NESDIS/VIIRS vegetation fraction to further improve land surface representativeness.

Case, Jonathan L.↗
NASA NTRS2013

Initial Assessment of a Variable-Camber Continuous Trailing-Edge Flap System on a Rigid Wing for Drag Reduction in Subsonic Cruise

In this paper, we describe an initial optimization study of a Variable-Camber Continuous Trailing-Edge Flap (VCCTEF) system. The VCCTEF provides a light-weight control system for aircraft with long flexible wings, providing efficient high-lift capability for takeoff and landing, and greater efficiency with reduced drag at cruising flight by considering the effects of aeroelastic wing deformations in the control law. The VCCTEF system is comprised of a large number of distributed and individually-actuatable control surfaces that are constrained in movement relative to neighboring surfaces, and are non-trivially coupled through structural aeroelastic dynamics. Minimzation of drag results in a constrained, coupled, non-linear optimization over a high-dimension search space. In this paper, we describe the modeling, analysis, and optimization of the VCCTEF system control inputs for minimum drag in cruise. The purpose of this initial study is to quantify the expected benefits of the system concept. The scope of this analysis is limited to consideration of a rigid wing without structural flexibility in a steady-state cruise condition at various fuel weights. For analysis, we developed an optimization engine that couples geometric synthesis with vortex-lattice analysis to automate the optimization procedure. In this paper, we present and describe the VCCTEF system concept, optimization approach and tools, run-time performance, and results of the optimization at 20%, 50%, and 80% fuel load. This initial limited-scope study finds the VCCTEF system can potentially gain nearly 10% reduction in cruise drag, provides greater drag savings at lower operating weight, and efficiency is negatively impacted by the severity of relative constraints between control surfaces.

trailing edge flaps↗
NASA NTRS2012

A Comparison of Perturbed Initial Conditions and Multiphysics Ensembles in a Severe Weather Episode in Spain

Ensembles of numerical model forecasts are of interest to operational early warning forecasters as the spread of the ensemble provides an indication of the uncertainty of the alerts, and the mean value is deemed to outperform the forecasts of the individual models. This paper explores two ensembles on a severe weather episode in Spain, aiming to ascertain the relative usefulness of each one. One ensemble uses sensible choices of physical parameterizations (precipitation microphysics, land surface physics, and cumulus physics) while the other follows a perturbed initial conditions approach. The results show that, depending on the parameterizations, large differences can be expected in terms of storm location, spatial structure of the precipitation field, and rain intensity. It is also found that the spread of the perturbed initial conditions ensemble is smaller than the dispersion due to physical parameterizations. This confirms that in severe weather situations operational forecasts should address moist physics deficiencies to realize the full benefits of the ensemble approach, in addition to optimizing initial conditions. The results also provide insights into differences in simulations arising from ensembles of weather models using several combinations of different physical parameterizations.

severe weather↗
NASA NTRS2014

Exploring the Utility of the Planned CYGNSS Mission for Investigating the Initiation and Development of the Madden-Julian Oscillation

CYGNSS is a planned constellation consisting of multiple micro-satellites that leverage the Global Positioning System (GPS) to provide rapidly updated, high resolution (approx. 15-50 km, approx. 4 h) surface wind speeds (via bi-static scatterometry) over the tropical oceans in any weather condition, including heavy rainfall. The approach of the work to be presented at this conference is to utilize a limited-domain, cloud-system resolving model (Weather Research and Forecasting or WRF) and its attendant data assimilation scheme (Three-Dimensional Variational Assimilation or 3DVAR) to investigate the utility of the CYGNSS mission for helping characterize key convectiveto- mesoscale processes - such as surface evaporation, moisture advection and convergence, and upscale development of precipitation systems - that help drive the initiation and development of the Madden-Julian Oscillation (MJO) in the equatorial Indian Ocean. The proposed work will focus on three scientific objectives. Objective 1 is to produce a high-resolution surface wind dataset resolution (approx. 0.5 h, approx. 1-4 km) for multiple MJO onsets using WRF-assimilated winds and other data from the DYNAmics of the MJO (DYNAMO) field campaign, which took place during October 2011 - March 2012. Objective 2 is to study the variability of surface winds during MJO onsets at temporal and spatial scales of finer resolution than future CYGNSS data. The goal is to understand how sub-CYGNSS-resolution processes will shape the observations made by the satellite constellation. Objective 3 is to ingest simulated CYGNSS data into the WRF model in order to perform observing system simulation experiments (OSSEs). These will be used to test and quantify the potential beneficial effects provided by CYGNSS, particularly for characterizing the physical processes driving convective organization and upscale development during the initiation and development of the MJO. The proposed research is ideal for answering important questions about the CYGNSS mission, such as the representativeness of surface wind retrievals in the context of the complex airflow processes that occur during heavy precipitation, as well as the tradeoffs in retrieval accuracy that result from finer spatial resolution of the CYGNSS winds versus increased errors/noisiness in those data. Research plans and initial progress toward these objectives will be presented.

Lang, Timothy↗
NASA NTRS2015

Model Forecast Skill and Sensitivity to Initial Conditions in the Seasonal Sea Ice Outlook

We explore the skill of predictions of September Arctic sea ice extent from dynamical models participating in the Sea Ice Outlook (SIO). Forecasts submitted in August, at roughly 2 month lead times, are skillful. However, skill is lower in forecasts submitted to SIO, which began in 2008, than in hindcasts (retrospective forecasts) of the last few decades. The multimodel mean SIO predictions offer slightly higher skill than the single-model SIO predictions, but neither beats a damped persistence forecast at longer than 2 month lead times. The models are largely unsuccessful at predicting each other, indicating a large difference in model physics and/or initial conditions. Motivated by this, we perform an initial condition sensitivity experiment with four SIO models, applying a fixed −1 m perturbation to the initial sea ice thickness. The significant range of the response among the models suggests that different model physics make a significant contribution to forecast uncertainty.

Arctic Sea↗
NASA NTRS2015

Integrated Mission Simulation (IMSim): Multiphase Initialization Design with Late Joiners, Rejoiners and Federation Save & Restore

This document describes the design of the Integrated Mission Simulation (IMSim) federate multiphase initialization process. The main goal of multiphase initialization is to allow for data interdependencies during the federate initialization process. IMSim uses the High Level Architecture (HLA) IEEE 1516 [1] to provide the communication and coordination between the distributed parts of the simulation. They are implemented using the Runtime Infrastructure (RTI) from Pitch Technologies AB. This document assumes a basic understanding of IEEE 1516 HLA, and C++ programming. In addition, there are several subtle points in working with IEEE 1516 and the Pitch RTI that need to be understood, which are covered in Appendix A. Please note the C++ code samples shown in this document are for the IEEE 1516-2000 standard.

Dexter, Daniel E.↗
NASA NTRS2016

Initial Navigation Alignment of Optical Instruments on GOES-R

Post-launch alignment errors for the Advanced Baseline Imager (ABI) and Geospatial Lightning Mapper (GLM) on GOES-R may be too large for the image navigation and registration (INR) processing algorithms to function without an initial adjustment to calibration parameters. We present an approach that leverages a combination of user-selected image-to-image tie points and image correlation algorithms to estimate this initial launch-induced offset and calculate adjustments to the Line of Sight Motion Compensation (LMC) parameters. We also present an approach to generate synthetic test images, to which shifts and rotations of known magnitude are applied. Results of applying the initial alignment tools to a subset of these synthetic test images are presented. The results for both ABI and GLM are within the specifications established for these tools, and indicate that application of these tools during the post-launch test (PLT) phase of GOES-R operations will enable the automated INR algorithms for both instruments to function as intended.

geolocation↗
NASA NTRS2017

The South/Southeast Asia Research Initiative (SARI) Update and Meeting Objectives

Land Use/Cover Change (LU/CC) is one of the most important types of environmental change in South and Southeast Asian countries. Several studies suggest that LU/CC in these countries is in large part driven by population growth and economic development. In the region, changes that are most common include urban expansion, agricultural land loss, land abandonment, deforestation, logging, reforestation, etc. To address the research needs and priorities in the region, a regional initiative entitled South Southeast Asia Regional Initiative (SARI) has been developed involving US and regional scientists. The initiative is funded by NASA Land Cover, Land Use Change program. The goal of SARI is to integrate state-of-the-art remote sensing, natural sciences, engineering and social sciences to enrich LU/CC science in South Southeast Asian countries. In the presentation, LU/CC change research in SARI countries will be highlighted including the drivers of change. For example, in South Asia, forest cover has been increasing in countries like India, Nepal and Bhutan due to sustainable afforestation measures; whereas, large-scale deforestation in Southeast Asian countries is still continuing, due to oil palm plantation expansion driven by the international market demand in Malaysia and Indonesia. With respect to urbanization, South and Southeast Asian countries contain 23 megacities, each with more than 10 million people. Rapid urbanization is driving agricultural land loss and agricultural intensification has been increasing due to less availability of land for growing food crops such as in India, Vietnam, and Thailand. The drivers of LUCC vary widely in the region and include such factors as land tenure, local economic development, government policies, inappropriate land management, land speculation, improved road networks, etc. In addition, variability in the weather, climate, and socioeconomic factors also drive LU/CC resulting in disruptions of biogeochemical cycles, radiation and the surface energy balance of the atmosphere. The presentation will also highlight SARI collaborative activities with space agencies, universities and non-government organizations including data sharing mechanisms in the region.

Research↗
NASA NTRS2017

Future Directions of the National Nanotechnology Initiative - NNI 2.0

The National Nanotechnology Initiative is a collaboration of 20 Federal agencies and departments with shared interests in nanotechnology research, development and commercialization. These agencies recognize that the ability to understand and exploit the novel phenomena that occur at the nanoscale will enabled the development of new materials and devices with properties and performance that far exceeds that of conventional systems. Due to the combined investments of the Federal government, now close to $24B, and those of industry, nanotechnology has moved out of the laboratory and into commercial products that are enhancing our daily lives. Nanotechnology-based discoveries are poised to revolutionize the way we diagnose and treat disease, radically improve the energy efficiency of aircraft and ground transportation systems, and will someday enable human exploration of Mars. This presentation will provide an overview of the National Nanotechnology Initiative, highlight some accomplishments in nanotechnology research and development, and discuss the future of the initiative.

nanotechnology↗
NASA NTRS2019

NASA's Digital Transformation (DT) Initiative

NASA's Digital Transformation (DT) Initiative will dramatically enhance NASA's mission impact by reinventing mission and mission support processes, products, and capabilities, enabled by an innovation culture, digital-savvy workforce, and advanced digital technologies, building on a foundation of modern data management and IT security. This presentation, as part of a conference panel, provides an overview of NASA's DT Initiative, and describes how the Initiative supports an "antidisciplinary" future, where the greatest mission transformation opportunities will be found at the intersections and mergers of multiple disciplines.

Biegel, Bryan↗
NASA NTRS2019

The Role of Oceanic Processes in the Initiation of Boreal Winter Intraseasonal Oscillations over the Indian Ocean

Observational analyses and a hierarchy of ocean general circulation model (OGCM) experiments were performed to understand the influence of oceanic processes on the warm sea surface temperature anomalies (SSTAs) prior to the convection initiation of boreal winter intraseasonal oscillations (ISOs), including the Madden-Julian Oscillation (MJO), in the equatorial Indian Ocean. We found 39 strong ISOs that passed over the Indian Ocean Warm Pool region during the November-April season of the 2001-2012 period. 17/39 ISO events initiated in the Seychelles-Chagos Thermocline Ridge (SCTR) before propagating eastward; the remaining events initiated in the southern Arabian Sea (6) or Warm Pool (16) regions. The SCTR event set was notable in that it contained more global-scale MJOs (71-76%), as defined by the RMM and OMI indices, than the WP events (25-44%). Additionally, ~24% (44%) of the SCTR (Warm Pool) events were preceded by strong oceanic process-induced SSTAs of similar magnitude to those of shortwave radiative and turbulent heat fluxes. The Arabian Sea events, however, were not associated with statistically significant SSTA signals prior to convection. Based on a mixed layer heat budget analysis, entrainment and upwelling reduction were the dominant oceanic processes contributing to the warming, in contrast with boreal summer, when horizontal advection dominated. We examined several case studies, including primary MJO events, where oceanic Rossby waves were associated with the entrainment and upwelling reduction. Two simple atmospheric boundary layer convergence models revealed that the SSTAs contributed at least half of the total convergence and suggested that the ocean dynamical effect was responsible for the majority of SSTA-forced convergence for those case studies. These results underscore the need for climate prediction models to accurately represent the ocean structure and processes to include the effects of oceanic predictors.

West, B. Jason↗
NASA NTRSDate not supplied

Initiation and Propagation of Skin/Stiffener Separation in Postbuckled Structures Subjected to Cyclic Loads

A methodology is proposed to evaluate experimentally and numerically the initiation and propagation of skin/stiffener separation in postbuckled panels subjected to cyclic loads. The response mechanisms that characterize skin/stiffener separation were investigated using a three point bend (3PB) test specimen, which is a simple specimen consisting of a laminate representing the skin and a doubler representing the stiffener flange. The 3PB tests were performed under quasi-static and cyclic loads. A fatigue cohesive model was used to analyze the initiation and propagation of skin/stiffener separation in the 3PB. The results indicate that the fatigue cohesive model with model parameters obtained from quasi-static fracture tests can provide accurate predictions of initiation from a pristine state, and the rate of fatigue crack propagation for a variety of mode mixities, load levels, and stress ratios.

Carlos G Davila↗
NASA NTRSDate not supplied

Initiation and Propagation of Skin/Stiffener Separation in Postbuckled Structures

A methodology is proposed to experimentally and numerically evaluate the initiation and propagation of skin/stiffener separation in postbuckled panels subjected to cyclic loads. The response mechanisms that characterize skin/stiffener separation were investigated using a three point bend (3PB) test specimen, which is a simple specimen consisting of a laminate representing the skin and a doubler representing the stiffener flange. The 3PB tests were performed under quasi-static and cyclic loads. A fatigue cohesive model was used to analyze the initiation and propagation of skin/stiffener separation in the 3PB specimen. The results indicate that the fatigue cohesive model with model parameters obtained from quasi-static fracture tests can provide accurate predictions of initiation from a pristine state, and the rate of fatigue crack propagation for a variety of mode mixities, load levels, and stress ratios.

Carlos G. Dávila↗
NASA NTRS2020

GRACE Improves Seasonal Groundwater Forecast Initialization Over the United States

We evaluate the impact of Gravity Recovery and Climate Experiment data assimilation (GRACE-DA) on seasonal hydrological forecast initialization over the United States, focusing on groundwater storage. GRACE-based terrestrial water storage (TWS) estimates are assimilated into a land surface model for the2003–16 period. Three-month hindcast (i.e., forecast of past events) simulations are initialized using states from the reference (no data assimilation) and GRACE-DA runs. Differences between the two initial hydrological condition (IHC) sets are evaluated for two forecast techniques at 305 wells where depth to water table measurements are available. Results show that using GRACE-DA-based IHC improves seasonal groundwater forecast performance in terms of both RMSE and correlation. While most regions show improvement, degradation is common in the High Plains, where withdrawals for irrigation practices affect groundwater variability more strongly than the weather variability, which demonstrates the need for simulating such activities. These findings contribute to recent efforts toward an improved U.S. drought monitoring and forecast system.

Augusto Getirana↗
NASA NTRS2020

Satellite Gravimetry Improves Seasonal Streamflow Forecast Initialization in Africa

West Africa is one of the poorest regions in the world and highly vulnerable to extreme hydrological events due to the lack of reliable monitoring and forecast systems. For the first time, we demonstrate that initial hydrological conditions informed by satellite-based terrestrial water storage (TWS) estimates improve seasonal streamflow forecasts. TWS variability detected by the Gravity Recovery and Climate Experiment (GRACE) satellites is assimilated into a land surface model during 2003–2016 and used to initialize 6-month hindcasts (i.e., forecasts of past events) during West Africa's wet seasons. We find that GRACE data assimilation (DA) generally increases groundwater and soil moisture storage in the region, resulting in increased evapotranspiration and reduced total runoff. Total runoff is particularly lower at the headwaters of the Niger River, positively impacting streamflow simulations and hindcast initializations. Compared to simulations without GRACE-DA, hindcasts are notably improved at locations draining from large basin areas, in particular, over the Niger River basin, which is consistent with GRACE's coarse spatial resolution. The long memory of groundwater and deep soil moisture, two main TWS components updated by GRACE-DA, is reflected in prolonged improvements in the streamflow hindcasts. Model accuracy at Niamey, Niger, the most populated city where streamflow observations are available, improved up to 33% during the flood season. These new findings directly contribute to ongoing developments in food security, flood potential forecast, and water-related disaster warning systems for Africa.

Augusto Getirana↗
NASA NTRSDate not supplied

Dissemination of Global Flood Information Through Nasa Disasters Program Global Initiative for Flood Forecasting and Alerting (GIFFT)

The Global Initiative for Flood Forecasting and Alerting (GIFFT) is an initiative to disseminate flood products from different sensors to global stakeholders via the Pacific Disaster Center’s (PDC) DisasterAWARE®, the NASA Disasters Mapping Portal and potentially other mechanisms. GIFFT will also generate an integrated product(s) using ensembled hydrologic models and Earth observation derived flood outputs to stakeholders globally. This initiative combines the results of several Disasters Program funded projects that focus on flood forecasting, flood severity estimation, post-event flood mapping, flooddepth estimation and resulting flood severity using remote sensing-based flood information derived from SAR and optical imagery. PDC’s DisasterAWARE platform is a global multi-hazard alerting platform that currently incorporatesModel of Models (MoM) outputs as flood “incidents,” visually depicting potential floods in the context ofpopulation and infrastructure that may become affected. Automated procedures are being developed tocategorize MoM outputs as DisasterAWARE “hazards,” allowing for their dissemination to users alongwith other flood products that assess potential impacts. PDC’s stakeholders include UN, DoD, FEMA andtheir equivalents around the world. Additionally, the DisasterALERT mobile platform has 2 million usersworldwide and is a fully functional and sustained platform used to disseminate alerts and analyticalproducts for 18 different hazard types. GIFFT has incorporated HydroSAR products that will bedistributed via DisasterAWARE.

remote sensing↗
NASA NTRSDate not supplied

AI Foundation Models for Science: An Open Collaborative Initiative

Foundation Models (FMs), AI models designed to replace task-specific models, are increasingly being recognized for their versatility across numerous downstream applications. These models, trained using self-supervised techniques on any type of sequence data, circumvent the need for large annotated datasets, a major bottleneck in traditional AI model development. FMs can be applied to downstream tasks using few-shot learning and fine-tuning, significantly reducing the need for large labeled training datasets and computational resources. However, the development of FMs requires substantial resources, including access to data and compute power, expertise in the latest models, and specialized scientific knowledge for systematic evaluation. It is challenging for a single group to possess all these capabilities. To address this, NASA IMPACT has initiated an open collaborative effort, leveraging partnerships with the private sector and other groups within and outside NASA, to jointly build FMs. The overarching goal is to develop a consistent and collaborative approach to building FMs for high-value science datasets. This initiative has fostered collaboration within NASA and with external partners, including IBM Research, Clark University, DOE’s ORNL, ESA, and USGS. The effort focuses on identifying key datasets with a wide range of downstream applications, pretraining and building FMs using modified transformer architectures, evaluating compute infrastructure needs, and sharing models, pretraining and fine-tuning code, and data with the community. Furthermore, it aims to train the Earth science community to fine-tune these models for various downstream applications. Our initial effort resulted in the creation of a 100 million parameter HLS Geospatial Model within six months, which was released on HuggingFace. We are now expanding our scope to include data from weather and climate models and investigating multimodal models. We invite those interested in participating in this effort to join us by sharing their use cases, expertise, or data.

Rahul Ramachandran↗