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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 973 records · Page 54

Synergistic and Collaborative Development Strategies for FV3 Powered Next Generation Unified Global Modeling System

The GFDL (Geophysical Fluid Dynamics Laboratory, NOAA - National Oceanic and Atmospheric Administration) Finite-­Volume Cubed-Sphere Dynamical Core (FV3) is a scalable and flexible dynamical core capable of both hydrostatic and non-hydrostatic atmospheric simulations. FV3 has been chosen as the dynamical core for the Next Generation Global Prediction System project (NGGPS), designed to upgrade the current NCEP (National Centers for Environmental Prediction, NOAA) operational Global Forecast System (GFS) to run as a unified, fully-coupled system in NOAA's Environmental Modeling System infrastructure. FV3 dynamic core has a long history of serving as the main engine for global atmospheric models at various Government and Academic Research Laboratories including NOAA: GFDL Climate Modeling Suite (AM4 (Atmosphere Modeling 4), CM4 (Climate Model 4) ESM4 (Earth System Model 4), Hiram (HIgh Resolution Atmospheric Model)); NASA: GMAO (Global Modeling and Assimilation Office) Goddard Earth Observing System Model (GEOS); and NCAR (National Center for Atmospheric Research) Community Earth System Model (CESM). The three primary stakeholders in FV3 (GFDL, GMAO, EMC (Environmental Modeling Center - NOAA)) have embarked on synergistic and collaborative strategies with focus on the advancement of non-hydrostratic dynamic core, physics, chemistry, and data assimilation efforts, leveraging collective strengths of each of the partnering agencies. This talk presents the ongoing plans for model advancements at GFDL, GMAO and EMC, with special emphasis on contributions towards developing community based unified global modeling system for operational and research applications at respective organizations. Future plans include extending the collaborations to the development of earth system components including GMAO's aerosol chemistry models (GOCART/MAM (Goddard Chemistry Aerosol Radiation and Transport / Modal Aerosol Model)), Land Information System (LIS), and advanced data assimilation techniques; and GFDL's Modular Ocean Model (MOM) and Sea Ice Simulator (SIS) for transition to operations at NCEP.

Putman, William↗

Source Term Model for an Array of Vortex Generator Vanes

A source term model was developed for numerical simulations of an array of vortex generators. The source term models the side force created by a vortex generator being modeled. The model is obtained by introducing a side force to the momentum and energy equations that can adjust its strength automatically based on a local flow. The model was tested and calibrated by comparing data from numerical simulations and experiments of a single low-profile vortex generator vane, which is only a fraction of the boundary layer thickness, over a flat plate. The source term model allowed a grid reduction of about seventy percent when compared with the numerical simulations performed on a fully gridded vortex generator without adversely affecting the development and capture of the vortex created. The source term model was able to predict the shape and size of the stream wise vorticity and velocity contours very well when compared with both numerical simulations and experimental data.

Buning, P. G.↗

Parametric System Model for a Stirling Radioisotope Generator

A Parametric System Model (PSM) was created in order to explore conceptual designs, the impact of component changes and power level on the performance of Stirling Radioisotope Generator (SRG). Using the General Purpose Heat Source (GPHS approximately 250 watt thermal) modules as the thermal building block around which a SRG is conceptualized, trade studies are performed to understand the importance of individual component scaling on isotope usage. Mathematical relationships based on heat and power throughput, temperature, mass and volume were developed for each of the required subsystems. The PSM uses these relationships to perform component and system level trades.

Modules↗

Parametric System Model for a Stirling Radioisotope Generator

A Parametric System Model (PSM) was created in order to explore conceptual designs, the impact of component changes and power level on the performance of the Stirling Radioisotope Generator (SRG). Using the General Purpose Heat Source (GPHS approximately 250 Wth) modules as the thermal building block from which a SRG is conceptualized, trade studies are performed to understand the importance of individual component scaling on isotope usage. Mathematical relationships based on heat and power throughput, temperature, mass, and volume were developed for each of the required subsystems. The PSM uses these relationships to perform component- and system-level trades.

Heat Transfer↗

On-board Limb-based Shape Modeling for Small Body Navigation

Missions to small bodies within our solar system are becoming more frequent. Generally, shape models of the target body are required to perform proximity operations as demonstrated by the OSIRIS-REx, Hayabusa2, and Rosetta missions. However, these missions required image downlinking to create high-resolution models on the ground. In some missions, especially small-sats, there may be data downlink data constraints, resulting in the inability to provide the large number of images needed for high-resolution shape models. A solution to this is the ability to generate shape models on-board during the approach to the target or initial proximity surveying. Current work implements a limb-based shape model routine that is able to be executed on a Raspberry Pi 1, which is similar to the processing capability to the flight computer on OSIRIS-REx, and that does not require low phase angle geometries. Initial shape model results generated from Bennu approach (Nov 2-3, 2018) show that the limb-based shape model agrees well with a 75-cm SPC shape model generated after Preliminary Survey; Results are: min difference -7.047m, max difference 17.347m, mean 1.122m, and RMS 3.219m. Further scenarios are presented herein.

Limb-based↗

A Deep Gravity model for mobility flows generation

The movements of individuals within and among cities influence critical aspects of our society, such as well-being, the spreading of epidemics, and the quality of the environment. When information about mobility flows is not available for a particular region of interest, we must rely on mathematical models to generate them. In this work, we propose Deep Gravity, an effective model to generate flow probabilities that exploits many features (e.g., land use, road network, transport, food, health facilities) extracted from voluntary geographic data, and uses deep neural networks to discover non-linear relationships between those features and mobility flows. Our experiments, conducted on mobility flows in England, Italy, and New York State, show that Deep Gravity achieves a significant increase in performance, especially in densely populated regions of interest, with respect to the classic gravity model and models that do not use deep neural networks or geographic data. Deep Gravity has good generalization capability, generating realistic flows also for geographic areas for which there is no data availability for training. Finally, we show how flows generated by Deep Gravity may be explained in terms of the geographic features and highlight crucial differences among the three considered countries interpreting the model’s prediction with explainable AI techniques.

97 MATHEMATICS AND COMPUTING↗

Methyl propyl ether combustion

Ethers are potential diesel blendstocks that have high cetane numbers and identified cost-effective production pathways. Among ethers, methyl propyl ether (MPE) is a small enough molecule to build a good detailed model for and a large enough molecule for studying key intramolecular hydrogen migrations involved in low-temperature feedback loops for larger ethers. In this study, a model was generated for the combustion of MPE from 600-900 K and 10-20 bar using the Reaction Mechanism Generator (RMG) package. Results from rapid compression machine (RCM) experiments were used to validate the kinetic model. At low temperatures, the generated model successfully captured the dominant low-temperature feedback loops. At higher temperatures, propanal is a major combustion intermediate for PME, suggesting that aldehydes likely play a significant role in larger ethers' combustion.

09 BIOMASS FUELS↗

Uncertainty Quantification of CFD Data Generated for a Model Scramjet Isolator Flowfield

Computational fluid dynamics is now considered to be an indispensable tool for the design and development of scramjet engine components. Unfortunately, the quantification of uncertainties is rarely addressed with anything other than sensitivity studies, so the degree of confidence associated with the numerical results remains exclusively with the subject matter expert that generated them. This practice must be replaced with a formal uncertainty quantification process for computational fluid dynamics to play an expanded role in the system design, development, and flight certification process. Given the limitations of current hypersonic ground test facilities, this expanded role is believed to be a requirement by some in the hypersonics community if scramjet engines are to be given serious consideration as a viable propulsion system. The present effort describes a simple, relatively low cost, nonintrusive approach to uncertainty quantification that includes the basic ingredients required to handle both aleatoric (random) and epistemic (lack of knowledge) sources of uncertainty. The nonintrusive nature of the approach allows the computational fluid dynamicist to perform the uncertainty quantification with the flow solver treated as a "black box". Moreover, a large fraction of the process can be automated, allowing the uncertainty assessment to be readily adapted into the engineering design and development workflow. In the present work, the approach is applied to a model scramjet isolator problem where the desire is to validate turbulence closure models in the presence of uncertainty. In this context, the relevant uncertainty sources are determined and accounted for to allow the analyst to delineate turbulence model-form errors from other sources of uncertainty associated with the simulation of the facility flow.

Baurle, R. A.↗

Marshall Space Flight Center surface modeling and grid generation applications

The Solid Rocket Motors (SRM) used by NASA to propel the Space Shuttle employ gimballing nozzles as a means for vehicular guidance during launch and ascent. Gimballing a nozzle renders the pressure field of the exhaust gases nonaxisymmetric. This has two effects: (1) it exerts a torque and side load on the nozzle; and (2) the exhaust gases flow circumferentially in the aft-dome region, thermally loading the flexible boot, case-to-nozzle joint, and casing insulation. The use of CFD models to simulate such flows is imperative in order to assess SRM design. The grids for these problems were constructed by obtaining information from drawings and tabulated coordinates. The 2D axisymmetric grids were designed and generated using the EZ-Surf and GEN2D surface and grid generation codes. These 2D grids were solved using codes such as FDNS, GASP, and MINT. These axisymmetric grids were rotated around the center-line to form 3D nongimballed grids. These were then gimballed around the pivot point and the gaps or overlaps resurfaced to obtain the final domains, which contained approximately 366,000 grid points. The 2D solutions were then rotated and manipulated as appropriate for geometry and used as initial guesses in the final solution. The analyses were used in answering questions about flight criteria.

Williams, Robert W.↗

The Impala's horn applied to posterior samples of Ti-6Al-4V strength model parameters

We have generated strength model parameters for the Preston-Tonks-Wallace (PTW) model of plastic deformation based on a collection of Ti-6Al-4V alloy data and a Bayesian framework. This data collected from the literature includes different chemistries and processes. The experiments include quasistatic compression, Split Hopkinson Pressure Bar (SHPB) compression, and Taylor cylinders. Here we use posterior parameter distributions applied to a hypothetical impact referred to as the Impala's horn. The Impala's horn is like a Taylor cylinder, but modified to have a conical pro le that is truncated before coming to a point. The smaller diameter at the impact end results in higher calculated strain rates and strains than the same velocity impact with the traditional Taylor profile. The modified geometry exercises the behavior of the strength model outside the range of conditions found in the calibration data. Here we sort posterior strength models based on their flow stress at characteristic values for this hypothetical deformation. Then we compare the performance of these posterior models based on two simple observable final state properties of the Impala's horn.

36 MATERIALS SCIENCE↗

Turbine modeling technique to generate off-design performance data for both single and multistage axial-flow turbines

This technique is applicable to larger axial flow turbines which may or may not incorporate variable geometry in the first stage stator. A user specified option will also permit the calculation of design point cooling flow levels and the corresponding change in turbine efficiency. The modeling technique was incorporated into a time sharing computer program in order to facilitate its use. Because this report contains a description of the input output data, values of typical inputs, and example cases, it is suitable as a user's manual.

Converse, G. L.↗

Validation and assimilation of Seasat altimeter wave heights using the WAM wave model

The third-generation wave model, WAM, is presently used to investigate the mutual consistency of the Seasat global data sets of scatterometer winds and altimeter wave heights for the complete Seasat period. While modeled and observed wave heights are in reasonable agreement on the global average, regional differences can be great and on occasion exceed 40 percent. These errors are primarily attributable to forcing wind field deficiencies; the friction velocities of the Goddard Laboratory for Atmospheres are found to be significantly underestimated in the high-wind belt of the Southern Hemisphere. A wave data assimilation scheme is presented in which the wave field is updated without change to the forcing wind field.

Bauer, Eva↗

Investigating Access Performance of Long Time Series with Restructured Big Model Data

Data sets generated by models are substantially increasing in volume, due to increases in spatial and temporal resolution, and the number of output variables. Many users wish to download subsetted data in preferred data formats and structures, as it is getting increasingly difficult to handle the original full-size data files. For example, application research users such as those involved with wind or solar energy, or extreme weather events are likely only interested in daily or hourly model data at a single point (or for a small area) for a long time period, and prefer to have the data downloaded in a single file. With native model file structures, such as hourly data from NASA Modern-Era Retrospective analysis for Research and Applications Version-2 (MERRA-2), it may take over 10 hours for the extraction of parameters-of-interest at a single point for 30 years. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is exploring methods to address this particular user need. One approach is to create value-added data by reconstructing the data files. Taking MERRA-2 data as an example, we have tested converting hourly data from one-day-per-file into different data cubes, such as one-month, or one-year. Performance is compared for reading local data files and accessing data through interoperable services, such as OPeNDAP. Results show that, compared to the original file structure, the new data cubes offer much better performance for accessing long time series. We have noticed that performance is associated with the cube size and structure, the compression method, and how the data are accessed. An optimized data cube structure will not only improve data access, but also may enable better online analysis services

reanalysis↗

Modeling Electrostatic Fields Generated by Internal Charging of Materials in Space Radiation Environments

Internal charging is a risk to spacecraft in energetic electron environments. DICTAT, NU MIT computational codes are the most widely used engineering tools for evaluating internal charging of insulator materials exposed to these environments. Engineering tools are designed for rapid evaluation of ESD threats, but there is a need for more physics based models for investigating the science of materials interactions with energetic electron environments. Current tools are limited by the physics included in the models and ease of user implementation .... additional development work is needed to improve models.

Minow, Joseph I.↗

Development of a metamodelling framework for building energy models with application to fifth-generation district heating and cooling networks

Fully defined physics-based building energy models can accurately represent building systems; however, generating models based on high-level parameters is time consuming and simulation time of complex models can be slow. This article discusses the development of a Metamodelling Framework to create metamodels from a building energy modelling dataset. The framework generates metamodels using either linear regression, random forests, or support vector regressions. A fifth-generation district heating and cooling system analysis use case was used to motivate the development of the framework. The use case required quick and accurate representations of annual building loads reported hourly. Typical annual building modelling approaches can result in a runtime of 10 min. The metamodels runtime was reduced to less than 10 s to load and run an annual simulation with user-defined covariates. The results of the metamodel performance and an abbreviated topology analysis based on the motivating use case will be presented.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

The impact of market design and clean energy incentives on strategic generation investments and resource adequacy in low-carbon electricity markets

Well-designed electricity markets play a crucial role in maintaining reliable electric power systems, which are critical in modern society. Here, this study examines the impact of different electricity market designs and clean energy incentive schemes on supporting renewable energy integration and achieving clean energy goals. To this end, we utilize a game-theoretical generation expansion planning model where generation companies make investment and retirement decisions to maximize their expected profit. The model is structured as an equilibrium problem with equilibrium constraints (EPEC) and solved using a diagonalization approach combined with progressive hedging. We analyze three types of electricity market designs: an energy-only market, a capacity market, and a clean energy market, and consider a wide range of market parameters resulting in 14 total scenarios. Wind and solar capacity comprise the majority of new investments in all considered scenarios, but the resultant system planning reserve margin (PRM) can differ significantly depending on market parameters. We also find that profit-driven investments lead to lower PRMs than a traditional system cost minimization approach. These individual scenario results further demonstrate how different market designs and clean energy incentive schemes may influence investor decision-making and impact resource adequacy throughout the clean energy transition.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗