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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 325 records · Page 18

Triangle Geometry Processing for Surface Modeling and Cartesian Grid Generation

Cartesian mesh generation is accomplished for component based geometries, by intersecting components subject to mesh generation to extract wetted surfaces with a geometry engine using adaptive precision arithmetic in a system which automatically breaks ties with respect to geometric degeneracies. During volume mesh generation, intersected surface triangulations are received to enable mesh generation with cell division of an initially coarse grid. The hexagonal cells are resolved, preserving the ability to directionally divide cells which are locally well aligned.

Aftosmis, Michael J.↗

PyDDA: A New Pythonic Wind Retrieval Package

PyDDA (Pythonic Direct Data Assimilation) is a new community framework aimed at wind retrievals that depends only upon utilities in the SciPy ecosystem such as scipy, numpy, and dask. It can support retrievals of winds using information from weather radar networks constrained by high resolution forecast models over grids that cover thousands of kilometers at kilometer-scale resolution. Unlike past wind retrieval packages, this package can be installed using anaconda for easy installation and, with a focus on ease of use can retrieve winds from gridded radar and model data with just a few lines of code. The package is currently available for download at https://github.com/openradar/PyDDA.

Radar↗

Strong Regional Influence of Climatic Forcing Datasets on Global Crop Model Ensembles

We present results from the Agricultural Model Intercomparison and Improvement Project (AgMIP) Global Gridded Crop Model Intercomparison (GGCMI) Phase I, which aligned 14 global gridded crop models (GGCMs) and 11 climatic forcing datasets (CFDs) in order to understand how the selection of climate data affects simulated historical crop productivity of maize, wheat, rice and soybean. Results show that CFDs demonstrate mean biases and differences in the probability of extreme events, with larger uncertainty around extreme precipitation and in regions where observational data for climate and crop systems are scarce. Countries where simulations correlate highly with reported FAO national production anomalies tend to have high correlations across most CFDs, whose influence we isolate using multi-GGCM ensembles for each CFD. Correlations compare favorably with the climate signal detected in other studies, although production in many countries is not primarily climate-limited (particularly for rice). Bias-adjusted CFDs most often were among the highest model-observation correlations, although all CFDs produced the highest correlation in at least one top-producing country. Analysis of larger multi-CFD-multi-GGCM ensembles (up to 91 members) shows benefits over the use of smaller subset of models in some regions and farming systems, although bigger is not always better. Our analysis suggests that global assessments should prioritize ensembles based on multiple crop models over multiple CFDs as long as a top-performing CFD is utilized for the focus region.

Agricultural Model Intercomparison and Improvement↗

A Model Predictive Control to Improve Grid Resilience

The following article details a model predictive control (MPC) to improve grid resilience when faced with variable generation resources. This topic is of significant interest to utility power systems where distributed intermittent energy sources will increase significantly and be relied on for electric grid ancillary services. Previous work on MPCs has focused on narrowly targeted control applications such as improving electric vehicle (EV) charging infrastructure or reducing the cost of integrating Energy Storage Systems (ESSs) into the grid. In contrast, this article develops a comprehensive treatment of the construction of an MPC tailored to electric grids and then applies it integration of intermittent energy resources. To accomplish this, the following article includes a description of a reduced order model (ROM) of an electric power grid based on a circuit model, an optimization formulation that describes the MPC, a collocation method for solving linear time-dependent differential algebraic equations (DAEs) that result from the ROM, and an overall strategy for iteratively refining the behavior of the MPC. Next, the algorithm is validated using two separate numerical experiments. First, the algorithm is compared to an existing MPC code and the results are verified by a numerically precise simulation. It is shown that this algorithm produces a control comparable to existing algorithms and the behavior of the control carefully respects the bounds specified. Second, the MPC is applied to a small nine bus system that contains a mix of turbine-spinning-machine-based and intermittent generation in order to demonstrate the algorithm’s utility for resource planning and control of intermittent resources. This study demonstrates how the MPC can be tuned to change the behavior of the control, which can then assist with the integration of intermittent resources into the grid. The emphasis throughout the paper is to provide systematic treatment of the topic and produce a novel nonlinear control compatible design framework applicable to electric grids and the control of variable resources. This differs from the more targeted application-based focus in most presentations.

microgrid↗

Space-time modeling using environmental constraints in a mobile robot system

Grid-based models of a robot's local environment have been used by many researchers building mobile robot control systems. The attraction of grid-based models is their clear parallel between the internal model and the external world. However, the discrete nature of such representations does not match well with the continuous nature of actions and usually serves to limit the abilities of the robot. This work describes a spatial modeling system that extracts information from a grid-based representation to form a symbolic representation of the robot's local environment. The approach makes a separation between the representation provided by the sensing system and the representation used by the action system. Separation allows asynchronous operation between sensing and action in a mobile robot, as well as the generation of a more continuous representation upon which to base actions.

Slack, Marc G.↗

Representing the Sub-Grid Heterogeneity of Surface Precipitation in A General Circulation Model

Precipitation variability on spatial scales smaller than a typical general circulation model (GCM) grid box is often neglected, with the grid-mean precipitation rate being applied uniformly to underlying surface tiles. This reduces the extrema seen by the surface, with corresponding reductions in surface runoff and altered land-atmosphere fluxes. Here we present a novel approach to stochastically distribute precipitation across sub-grid surface tiles within a GCM. Based on 4 km Stage IV precipitation data, the scheme parameterizes the dry area fraction as a function of grid mean precipitation rate, and defines the relative distribution of intensities across non-dry surface tiles. To incorporate memory and mimic the persistence of precipitating storms, the relative intensity assigned to each sub-grid tile is determined by an autoregressive process. Using single column experiments, the scheme is shown to reproduce observed precipitation statistics at the scale of model surface tiles. We also document impacts on surface hydrology and energy partitioning, with notable increases in precipitation runoff, surface temperature variance, and the Bowen ratio.

GCM↗

(GO)2-SIM: a GCM-Oriented Ground-Observation Forward-Simulator Framework for Objective Evaluation of Cloud and Precipitation Phase

General circulation model (GCM) evaluation using ground-based observations is complicated by inconsistencies in hydrometeor and phase definitions. Here we describe (GO)2-SIM, a forward simulator designed for objective hydrometeor-phase evaluation, and assess its performance over the North Slope of Alaska using a 1-year GCM simulation. For uncertainty assessment, 18 empirical relationships are used to convert model grid-average hydrometeor (liquid and ice, cloud, and precipitation) water contents to zenith polarimetric micropulse lidar and Ka-band Doppler radar measurements, producing an ensemble of 576 forward-simulation realizations. Sensor limitations are represented in forward space to objectively remove from consideration model grid cells with undetectable hydrometeor mixing ratios, some of which may correspond to numerical noise.Phase classification in forward space is complicated by the inability of sensors to measure ice and liquid signals distinctly. However, signatures exist in lidar–radar space such that thresholds on observables can be objectively estimated and related to hydrometeor phase. The proposed phase-classification technique leads to misclassification in fewer than 8% of hydrometeor-containing grid cells. Such misclassifications arise because, while the radar is capable of detecting mixed-phase conditions, it can mistake water- for ice-dominated layers. However, applying the same classification algorithm to forward-simulated and observed fields should generate hydrometeor-phase statistics with similar uncertainty. Alternatively, choosing to disregard how sensors define hydrometeor phase leads to frequency of occurrence discrepancies of up to 40%. So, while hydrometeor-phase maps determined in forward space are very different from model "reality" they capture the information sensors can provide and thereby enable objective model evaluation.

Lamer, K.↗

Evaluation of grid generation technologies from an applied perspective

An analysis of the grid generation process from the point of view of an applied CFD engineer is given. Issues addressed include geometric modeling, structured grid generation, unstructured grid generation, hybrid grid generation and use of virtual parts libraries in large parametric analysis projects. The analysis is geared towards comparing the effective turn around time for specific grid generation and CFD projects. The conclusion was made that a single grid generation methodology is not universally suited for all CFD applications due to both limitations in grid generation and flow solver technology. A new geometric modeling and grid generation tool, CFD-GEOM, is introduced to effectively integrate the geometric modeling process to the various grid generation methodologies including structured, unstructured, and hybrid procedures. The full integration of the geometric modeling and grid generation allows implementation of extremely efficient updating procedures, a necessary requirement for large parametric analysis projects. The concept of using virtual parts libraries in conjunction with hybrid grids for large parametric analysis projects is also introduced to improve the efficiency of the applied CFD engineer.

Hufford, Gary S.↗

Sparse-grid discontinuous Galerkin methods for the Vlasov–Poisson–Lenard–Bernstein model

Sparse-grid methods have recently gained interest in reducing the computational cost of solving high-dimensional kinetic equations. In this paper, we construct adaptive and hybrid sparse-grid methods for the Vlasov–Poisson–Lenard–Bernstein (VPLB) model. This model has applications to plasma physics and is simulated in two reduced geometries: a 0x3v space homogeneous geometry and a 1x3v slab geometry. Here we use the discontinuous Galerkin (DG) method as a base discretization due to its high-order accuracy and ability to preserve important structural properties of partial differential equations. We utilize a multiwavelet basis expansion to determine the sparse-grid basis and the adaptive mesh criteria. We analyze the proposed sparse-grid methods on a suite of three test problems by computing the savings afforded by sparse-grids in comparison to standard solutions of the DG method. The results are obtained using the adaptive sparse-grid discretization library ASGarD.

97 MATHEMATICS AND COMPUTING↗

Reynolds-Averaged Navier-Stokes Simulations of Two Partial-Span Flap Wing Experiments

Structured Reynolds Averaged Navier-Stokes simulations of two partial-span flap wing experiments were performed. The high-lift aerodynamic and aeroacoustic wind-tunnel experiments were conducted at both the NASA Ames 7-by 10-Foot Wind Tunnel and at the NASA Langley Quiet Flow Facility. The purpose of these tests was to accurately document the acoustic and aerodynamic characteristics associated with the principle airframe noise sources, including flap side-edge noise. Specific measurements were taken that can be used to validate analytic and computational models of the noise sources and associated aerodynamic for configurations and conditions approximating flight for transport aircraft. The numerical results are used to both calibrate a widely used CFD code, CFL3D, and to obtain details of flap side-edge flow features not discernible from experimental observations. Both experimental set-ups were numerically modeled by using multiple block structured grids. Various turbulence models, grid block-interface interaction methods and grid topologies were implemented. Numerical results of both simulations are in excellent agreement with experimental measurements and flow visualization observations. The flow field in the flap-edge region was adequately resolved to discern some crucial information about the flow physics and to substantiate the merger of the two vortical structures. As a result of these investigations, airframe noise modelers have proposed various simplified models which use the results obtained from the steady-state computations as input.

Takalluk, M. A.↗

Constraints and Potentials of Future Irrigation Water Availability on Agricultural Production Under Climate Change

Freshwater availability is relevant to almost all socioeconomic and environmental impacts of climate and demographic change and their implications for sustainability. We compare ensembles of water supply and demand projections driven by ensemble output from five global climate models. Our results suggest reasons for concern. Direct climate impacts to maize, soybean, wheat, and rice involve losses of 400–2,600 Pcal (8–43% of present-day total). Freshwater limitations in some heavily irrigated regions could necessitate reversion of 20–60 Mha of cropland from irrigated to rainfed management, and a further loss of 600–2,900 Pcal. Freshwater abundance in other regions could help ameliorate these losses, but substantial investment in infrastructure would be required. We compare ensembles of water supply and demand projections from 10 global hydrological models and six global gridded crop models. These are produced as part of the Inter-Sectoral Impacts Model Intercomparison Project, with coordination from the Agricultural Model Intercomparison and Improvement Project, and driven by outputs of general circulation models run under representative concentration pathway 8.5 as part of the Fifth Coupled Model Intercomparison Project. Models project that direct climate impacts to maize, soybean, wheat, and rice involve losses of 400–1,400 Pcal (8–24% of present-day total) when CO2 fertilization effects are accounted for or 1,400–2,600 Pcal (24–43%) otherwise. Freshwater limitations in some irrigated regions (western United States; China; and West, South, and Central Asia) could necessitate the reversion of 20–60 Mha of cropland from irrigated to rainfed management by end-of-century, and a further loss of 600–2,900 Pcal of food production. In other regions (northern/eastern United States, parts of South America, much of Europe, and South East Asia) surplus water supply could in principle support a net increase in irrigation, although substantial investments in irrigation infrastructure would be required.

agriculture↗

A Library of ATMO Forward Model Transmission Spectra for Hot Jupiter Exoplanets

We present a grid of forward model transmission spectra, adopting an isothermal temperature-pressure profile, alongside corresponding equilibrium chemical abundances for 117 observationally significant hot exoplanets (equilibrium temperatures of 547-2710 K). This model grid has been developed using a 1D radiative-convective-chemical equilibrium model termed ATMO, with up-to-date high-temperature opacities. We present an interpretation of observations of 10 exoplanets, including best-fitting parameters and X(exp 2) maps. In agreement with previous works, we find a continuum from clear to hazy/cloudy atmospheres for this sample of hot Jupiters. The data for all the 10 planets are consistent with subsolar to solar C/O ratio, 0.005 to 10 times solar metallicity and water rather than methane-dominated infrared spectra. We then explore the range of simulated atmospheric spectra for different exoplanets, based on characteristics such as temperature, metallicity, C/O ratio, haziness and cloudiness. We find a transition value for the metallicity between 10 and 50 times solar, which leads to substantial changes in the transmission spectra. We also find a transition value of C/O ratio, from water to carbon species dominated infrared spectra, as found by previous works, revealing a temperature dependence of this transition point ranging from approximately 0.56 to approximately 1-1.3 for equilibrium temperatures from approximately 900 to approximately 2600 K. We highlight the potential of the spectral features of HCN and C2H2 to constrain the metallicities and C/O ratios of planets, using James Webb Space Telescope (JWST) observations. Finally, our entire grid (approximately 460 000 simulations) is publicly available and can be used directly with the JWST simulator PandExo for planning observations.

techniques: spectroscopic – planets and satellit↗

Distribution System Dataset Generator for AI Applications [SWR-24-75]

This software is a simple, light-weight python package to generate pytorch compatible machine learning graph dataset representing electric power distribution system. User is able to use these graph datasets to test their graph generation artificial intelligence (AI) models, link prediction AI models, graph classification AI models and so much more. This package uses grid-data-models (https://github.com/NREL-Distribution-Suites/grid-data-models) as input data format for power distribution system. NREL-Ditto (https://github.com/NREL-Distribution-Suites/ditto) tool can be leveraged to transform popular distribution system file formats such as opendss, cyme and synergi to grid-data-models.

Duwadi, Kapil↗

Mathematical model of the current density for the 30-cm engineering model thruster

Mathematical models are presented for both the singly and doubly charged ion current densities downstream of the 30-cm engineering model thruster with 0.5% compensated dished grids. These models are based on the experimental measurements of Vahrenkamp at a 2-amp ion beam operating condition. The cylindrically symmetric beam of constant velocity ions is modeled with continuous radial source and focusing functions across 'plane' grids with similar angular distribution functions. A computer program is used to evaluate the double integral for current densities in the near field and to obtain a far field approximation beyond 10 grid radii. The utility of the model is demonstrated for (1) calculating the directed thrust and (2) determining the impingement levels on various spacecraft surfaces from a two-axis gimballed, 2 x 3 thruster array.

Cuffel, R. F.↗

Per-phase Phasor Modeling of GFL and GFM Inverters for Distribution System Dynamic Studies

A significant increase in inverter-based distributed energy resources (DERs) is expected in the near future. Existing electromagnetic models and sequential electromechanical models of DERs supporting dynamic analysis cannot be extended to largescale three-phase distribution systems usually with unbalanced construction. As such, there is a need for appropriate industry models that can support distribution system dynamic studies. This paper describes the latest phasor models of grid-following (GFL) and grid-forming (GFM) inverters that can capture distribution system dynamics under grid disturbances. The overall modeling performance is examined and compared with results from other platforms such as controller hardware-in-the-loop (CHIL), MATLAB/Simulink and PSCAD with electromagnetic transient (EMT) and/or phasor simulation capabilities under balanced and unbalanced faults.

Distribution system, Grid modelling, GridLAB-D, Po↗

Propulsion Simulations Using Advanced Turbulence Models with the Unstructured Grid CFD Tool, TetrUSS

A computational investigation has been completed to assess the capability of TetrUSS for exhaust nozzle flows. Three configurations were chosen for this study (1) an axisymmetric supersonic jet, (2) a transonic axisymmetric boattail with solid sting operated at different Reynolds number and Mach number, and (3) an isolated non-axisymmetric nacelle with a supersonic cruise nozzle. These configurations were chosen because existing experimental data provided a means for measuring the ability of TetrUSS for simulating complex nozzle flows. The main objective of this paper is to validate the implementation of advanced two-equation turbulence models in the unstructured-grid CFD code USM3D for propulsion flow cases. USM3D is the flow solver of the TetrUSS system. Three different turbulence models, namely, Menter Shear Stress Transport (SST), basic k epsilon, and the Spalart-Allmaras (SA) are used in the present study. The results are generally in agreement with other implementations of these models in structured-grid CFD codes. Results indicate that USM3D provides accurate simulations for complex aerodynamic configurations with propulsion integration.

Abdol-Hamid, Khaled S.↗

An interpretation of the spectral properties of hot hydrogen-rich white dwarfs with stratified H/He model atmospheres

A grid of stratified H/He model atmospheres applicable to the interpretation of the spectral properties of hot H-rich white dwarfs (WDs) is computed. Samples of hot DA WDs observed with Exosat and Einstein are analyzed using the models. Six out of six objects with T(eff) = 35,000 K or less do not show a EUV/soft X-ray flux deficiency and therefore can be understood solely in terms of pure hydrogen atmospheres. A majority of DA WDs hotter than this value do show a flux deficiency and thus require the presence of some absorbers in their atmospheres. It is shown that the Exosat broadband photometry of Feige 24 and G191 B2B cannot be explained in terms of stratified atmospheres. Absorption by heavy elements is certainly responsible for the required EUV/soft X-ray opacity source in these cases. However, the Exosat data are consistent with the hypothesis of stratified atmospheres in the four remaining objects.

Vennes, Stephane↗