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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 307 records · Page 17
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NASA NTRS2018

PURE: Scalable Phase Unwrapping with Spatial Redundant Arcs

Phase unwrapping is a key problem in many coherent imaging systems, such as syntheticapertureradar(SAR)interferometry. Ageneralformulationforredundant integration of finite differences for phase unwrapping (Costantini et al., 2010) was shown to produce a more reliable solution by exploiting redundant differential estimates. However, this technique requires a commercial linear programming solver for large-scale problems. For a linear cost function, we propose a method based on Dual Decomposition that breaks the given problem defined over a nonplanar graph into tractable sub-problems over planar subgraphs. We also propose a decomposition technique that exploits the underlying graph structure for solving thesub-problemsefficientlyandguaranteesasymptoticconvergencetotheglobally optimal solution. The experimental results demonstrate that the proposed approach is comparable to the existing state-of-the-art methods in terms of the estimate with a better runtime and memory footprint.

Lanka, Ravi↗
NASA NTRS2018

Fast Linearized Coronagraph Optimizer (FALCO) II: Optical Model Validation and Time Savings over Other Methods

We have developed the Fast Linearized Coronagraph Optimizer (FALCO), a new software toolbox for high-contrast, coronagraphic wavefront sensing and control. FALCO rapidly calculates the linearized deformable mirror (DM) response matrices, also called control Jacobians, and can be used for the design, simulation, or testbed operation of several types of coronagraphs. In this paper, we demonstrate that the optical propagation used in FALCO is accurate and matches PROPER. In addition, we demonstrate the drastic reduction in runtime when using FALCO for DM Jacobian calculations instead of the conventional method used, for example with a model of the Wide-Field Infrared Survey Telescope (WFIRST) Coronagraph Instrument (CGI). We then compare the relative accuracy between optical models in FALCO and PROPER.

Coker, Carl↗
NASA NTRS2018

Applications of the Dynamic N-Dimensional K-Vector

The n-dimensional k-vector (NDKV) is an appealing alternative to binary tress for resolving complex queries in large relational databases. The method has excelled in several applications involving static databases. The present paper extends the theory supporting the NDKV to handle dynamic databases, where the data is updated frequently. This includes deleting records, adding new entries, or editing existing elements. The merit of this new version of the NDKV, the dynamic n-dimensional k-vector (DNDKV), is that it is no longer necessary to recompute the entire k-vector (the main structure that indexes the data) every time a record changes. The algorithm updates the four constituents of the standard NDKV on the fly: the database, sorted database, index, and k-vector tables. As a result, the DNDKV becomes comparable in terms of capabilities and flexibility to stateof-the-art storage engines relying on structured query languages (SQL). The performance of the DNDKV is assessed by running typical read/write operations on a database that contains millions of pre-computed missions to celestial bodies. This database requires frequent updates whenever an orbit solution is refined or new bodies are discovered. The DNDKV is faster than rebuilding the k-vector tables completely, provided that the number of elements being added or removed is not excessively large. Direct runtime comparisons with MySQL suggest that the DNDKV is several times faster for reading but might be slower for writing and updating the database. One limit of the technique is the elements being added must be within the range of the current k-vector tables. If this is not the case, the technique cannot be used and the k-vector tables must be rebuilt from scratch.

Mortari, Daniele↗
NASA NTRS2018

BDDs on the Run

Runtime verification (RV) of first-order temporal logic must handle a potentially large amount of data, accumulated during the monitoring of an execution. The DEJAVU RV system represents data elements and relations using BDDs. This achieves a compact representation, which allows monitoring long executions. However, the potentially unbounded, and frequently very large amounts of data value scan,ultimately, limit the executions that can be monitored. We present an automatic method for “forgetting” data values when they no longer affect the RV verdict on an observed execution.We describe the algorithm and illustrate its operation through an example.

Peled, Doron↗
NASA NTRSDate not supplied

Engineering Software for Flight

This talk describes our efforts to improve the software engineering processes of the Copilot runtime verification framework so that the code generated can be used in UAS flights.

software engineering↗
NASA NTRS2021

Harmonized Emissions Component (HEMCO) 3.0 as a Versatile Emissions Component for Atmospheric Models: Application in the GEOS-Chem, NASA GEOS, WRF-GC, CESM2, NOAA GEFS-Aerosol, and NOAA UFS Models

Emissions are a central component of atmospheric chemistry models. The Harmonized Emissions Component (HEMCO) is a software component for computing emissions from a user-selected ensemble of emission inventories and algorithms. It allows users to re-grid, combine, overwrite, subset, and scale emissions from different inventories through a configuration file and with no change to the model source code. The configuration file also maps emissions to model species with appropriate units. HEMCO can operate in offline stand-alone mode, but more importantly it provides an online facility for models to compute emissions at runtime. HEMCO complies with the Earth System Modeling Framework (ESMF) for portability across models. We present a new version here, HEMCO 3.0, that features an improved three-layer architecture to facilitate implementation into any atmospheric model and improved capability for calculating emissions at any model resolution including multiscale and unstructured grids. The three-layer architecture of HEMCO 3.0 includes (1) the Data Input Layer that reads the configuration file and accesses the HEMCO library of emission inventories and other environmental data, (2) the HEMCO Core that computes emissions on the user-selected HEMCO grid, and (3) the Model Interface Layer that re-grids (if needed) and serves the data to the atmospheric model and also serves model data to the HEMCO Core for computing emissions dependent on model state (such as from dust or vegetation). The HEMCO Core is common to the implementation in all models, while the Data Input Layer and the Model Interface Layer are adaptable to the model environment. Default versions of the Data Input Layer and Model Interface Layer enable straightforward implementation of HEMCO in any simple model architecture, and options are available to disable features such as re-gridding that may be done by independent couplers in more complex architectures. The HEMCO library of emission inventories and algorithms is continuously enriched through user contributions so that new inventories can be immediately shared across models. HEMCO can also serve as a general data broker for models to process input data not only for emissions but for any gridded environmental datasets. We describe existing implementations of HEMCO 3.0 in (1) the GEOS-Chem “Classic” chemical transport model with shared-memory infrastructure, (2) the high-performance GEOS-Chem (GCHP) model with distributed-memory architecture, (3) the NASA GEOS Earth System Model (GEOS ESM), (4) the Weather Research and Forecasting model with GEOS-Chem (WRF-GC), (5) the Community Earth System Model Version 2 (CESM2), and (6) the NOAA Global Ensemble Forecast System – Aerosols (GEFS-Aerosols), as well as the planned implementation in the NOAA Unified Forecast System (UFS). Implementation of HEMCO in CESM2 contributes to the Multi-Scale Infrastructure for Chemistry and Aerosols (MUSICA) by providing a common emissions infrastructure to support different simulations of atmospheric chemistry across scales.

Haipeng Lin↗
NASA NTRS2021

Grid-Stretching Capability for the GEOS-Chem 13.0.0 Atmospheric Chemistry Model

Modeling atmospheric chemistry at fine resolution globally is computationally expensive; the capability to focus on specific geographic regions using a multi scale grid is desirable. Here, we develop, validate, and demonstrate stretched grids in the GEOS-Chem atmospheric chemistry model in its high-performance implementation (GCHP). These multiscale grids are specified at runtime by four parameters that offer users nimble control of the region that is refined and the resolution of the refinement. We validate the stretched-grid simulation versus global cubed-sphere simulations. We demonstrate the operation and flexibility of stretched-grid simulations with two case studies that compare simulated tropospheric NO2column densities from stretched-grid and cubed-sphere simulations to retrieved column densities from the TROPOspheric Monitoring Instrument (TROPOMI). The first case study uses a stretched grid with a broad refinement covering the contiguous US to produces imulated columns that perform similarly to a C180 (∼50 km) cubed-sphere simulation at less than one-ninth the computational expense. The second case study experiments with a large stretch-factor for a global stretched-grid simulation with a highly localized refinement with∼10 km resolution for California. We find that the refinement improves spatial agreement with TROPOMI columns compared to a C90 cubed-sphere simulation of comparable computational demands. Overall we find that stretched grids in GEOS-Chem are a practical tool for fine resolution regional- or continental-scale simulations of atmospheric chemistry. Stretched grids are available in GEOS-Chem version 13.0.0

GEOS-Chem↗
NASA NTRSDate not supplied

Minimum-Violation Traffic Management for Urban Air Mobility

Urban air mobility (UAM) refers to air transportation services in and over an urban area and has the potential to revolutionize mobility solutions. However, due to the projected scale of operations, current air traffic management (ATM) techniques are not viable. Increasingly autonomous systems are a pathway to accelerate the realization of UAM operations but must be fielded safely and efficiently. The heavily regulated, safety critical nature of aviation may lead to multiple, competing safety constraints that can be traded off based on the operational context. In this paper, we design a framework which allows for the scalable planning of a UAM ATM system. We formalize safety oriented constraints derived from FAA regulations by encoding them as temporal logic formulae. We then propose a method for UAM ATM that is both scalable and minimally violates the temporal logic constraints. Numerical results show that the runtime for our proposed algorithm is suitable for very large problems and is backed by theoretical guarantees of correctness with respect to given temporal logic constraints.

Urban Air Mobility↗
NASA NTRSDate not supplied

Initial Evaluation of CropManage Decision-Support Model for Vineyard ET Estimation

The CropManage(CM) decision-support web application was originally developed by U.C. Cooperative Extension to support evapotranspiration (ET) based irrigation scheduling and nutrient management of cool-season vegetables. The model uses prescribed crop phenology curves to develop daily estimates of fractional green canopy cover (Fc) within the field. Periodic Fc observations acquired by ground-based methods or imported from NASA’s Satellite Irrigation Management Support (SIMS) can be used to adjust the prescribed timeseries for such factors as weather anomalies or non-standard agronomic practice, as needed. Fc is then converted to daily crop coefficient (fraction of reference ET) values. The crop coefficient is combined with reference evapotranspiration, collected by the California Irrigation Management Information System, to derive daily ET estimates for the given field. Irrigation runtime recommendations are issued for a given date based on total ET since the last irrigation event (less any rainfall), and corrected for distribution uniformity of the water delivery system. In this project, CM was adapted to vineyards by adding sub-models to account for early-season depletion of stored soil moisture, cover crop presence, and intentional water stress. An initial trial was performed on a Central Coast winegrape vineyard, where an eddy covariance tower measured daily ET during from May-Dec 2020. Total ET for the period showed strong agreement between the tower-based measurements (443 mm) and the CM model (431 mm). The model tended to overestimate cumulative ET during mid-June by up to 30 mm (about 15%) and later underestimated cumulative ET by as much as 65 mm (about 23%) in late September, suggesting that additional model calibration is needed to improve simulation of within-season variability. Results will be reported for trials on additional vineyard sites conducted during the 2021 season.

Evaluation↗
NASA NTRSDate not supplied

Three-Dimensional Structure and Modeling of a Normal Bifurcated Shock Train from Experimental Measurements

An asymmetric, normal bifurcated shock train in a Mach 2 constant area, rectangular duct is investigated in the University of Michigan Direct Connect Isolator facility. High-speed schlieren imaging, wall static pressure measurements, surface oil flow visualization, and particle image velocimetry of the shock train are synthesized into a three-dimensional representation. This visualization is then used to inform the underlying flow physics of the distributed fluid dynamical processes along the shock train. The detailed, three-dimensional morphology of the flow profile entering the shock train is shown to have a significant impact on the separated flow morphology of the shock train. This results in a skewed supersonic core flow with alternating separation bubbles in the surrounding boundary layers. Finally, the efficacy of the prevailing pseudo-shock models in the literature is analyzed with the support of the available flow measurements. None are found to model both the pressure and streamwise Mach number profile of the UMDCI pseudo-shock. Note: This presentation is accompanied by the video presentation that can be downloaded for viewing and is formatted as an mp4 with a runtime of 10 min 15 secs.

Hypersonics↗
NASA NTRSDate not supplied

STEReO

STEReO brings together several technologies in Unmanned Aircraft Systems (UAS) Traffic Management (UTM), Autonomy, Communications, Human Factors, and Domain Expertise & Tools, aimed at providing scalability and flexibility, as well as operational resiliency to dynamic changes during a disaster event. Some of the concepts STEReO explores are: collaborative tools to ingest remote sensing information and distribute a common mission operating picture, apply ad-hoc communication networks to facilitate timely information sharing and communication of changes, vehicle-to-vehicle and onboard autonomy technologies ensure the safety and resiliency of operations, and apply NASA’s UAS traffic management system (UTM) as a public safety UAS Service Supplier (USS) to access and coordinate use of the airspace by both manned and unmanned operations. The potential benefits of STEReO include: standardized, cross-platform communication means increased interoperability and ease of cooperation/collaboration, increased situation awareness and common operating picture allow for earlier detection and decision making, and scalable to size and complexity of environment, operations, and mission objectives. This presentation gives an informational overview of the STEReO project to attendees of the Helicopter Association International (HAI) Aerial Firefighting Safety Conference. Note: Presentation slide 7 video is included in record as additional attachment, requires download of mp4 file, runtime 1 min 54 secs.

emergency response operations↗
NASA NTRS2021

NASA Ames Research Center Unitary Plan Wind Tunnel Fall 2018 Outage - Motor 1 Activity: Stator Shift

The Unitary Plan Wind Tunnel consists of the 11 x 11- Foot Transonic Wind Tunnel and the 9 x 7 foot Supersonic Wind Tunnel. The four 65,000hp electric motors that drive the wind tunnel compressors require periodic maintenance. In order to inspect the motors without the removal of drive shaft components, the stator must be shifted away from the motor. This process is referred to as "Stator Shift". Video is mp4 formatted with runtime of 2 mins 54 secs.

Wind Tunnel↗
NASA NTRSDate not supplied

Application of Advanced Earth Observations and Model Simulations to Improve Air Quality Monitoring in the Hindu-Kush-Himalayan Region

Air pollution is a serious environmental health concern in the Hindu Kush Himalayan (HKH) region of south-central Asia, as rapid industrialization and population growth have led to increased anthropogenic emissions from transportation, residential, industrial, energy, and biomass burning sources. Natural emissions from dust and forest fires are additional sources of air pollutants that can exacerbate air quality in the region. The combination of the complex pollutant mixtures and atmospherically stable weather conditions during the winter monsoon can visibility reductions and hazardous air quality from persistent haze episodes. The Kathmandu Valley is especially vulnerable to extreme haze issues due to the surrounding mountains that restrict air movement and retains pollutants in the atmosphere. This study uses state-of-the-art satellite observations and modeling capabilities in conjunction with ground-based networks to provide a comprehensive data toolkit for advancing air quality monitoring and forecasting decisions in the HKH region. The toolkit includes new generation satellite observations from the TROPOspheric Monitoring Instrument (TROPOMI), Geostationary Environment Monitoring Spectrometer (GEMS), and Advanced Meteorological Imager, which provide high spatiotemporal information on NO2, HCHO, SO2, O3, and aerosol optical depth (AOD). Particulate matter with diameters less than 2.5 micrometers (PM2.5) are derived from the satellite-retrieved AOD using ground-based observations and forecast model data. The satellite observations are also used to initialize and constrain forecast model systems designed for the HKH region. This talk will highlight the performance of the air quality toolkit for enhancing decision-making processes during exceptional air quality events in the region. Note: Presentation includes additional attachment of full presentation with sound and animation (best when viewed as slide show) with runtime of 15 min 32 secs

Aaron Naeger↗