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At least 685 records · Page 38

High-Efficiency Food Production in a Renewable Energy Based Micro-Grid Power System

Controlled Environment Agriculture (CEA) systems can be used to produce high-quality, desirable food year round, and the fresh produce can positively contribute to the health and well being of residents in communities with difficult supply logistics. While CEA has many positive outcomes for a remote community, the associated high electric demands have prohibited widespread implementation in what is typically already a fully subscribed power generation and distribution system. Recent advances in CEA technologies as well as renewable power generation, storage, and micro-grid management are increasing system efficiency and expanding the possibilities for enhancing community supporting infrastructure without increasing demands for outside supplied fuels. We will present examples of how new lighting, nutrient delivery, and energy management and control systems can enable significant increases in food production efficiency while maintaining high yields in CEA. Examples from Alaskan communities where initial incorporation of renewable power generation, energy storage and grid management techniques have already reduced diesel fuel consumption for electric generation by more than 40% and expanded grid capacity will be presented. We will discuss how renewable power generation, efficient grid management to extract maximum community service per kW, and novel energy storage approaches can expand the food production, water supply, waste treatment, sanitation and other community support services without traditional increases of consumable fuels supplied from outside the community. These capabilities offer communities with a range of choices to enhance their communities. The examples represent a synergy of technology advancement efforts to develop sustainable community support systems for future space-based human habitats and practical implementation of infrastructure components to increase efficiency and enhance health and well being in remote communities today and tomorrow.

Fuel↗

Best Practices for Unstructured Grid Shock-Fitting

Unstructured grid solvers have well-known issues predicting surface heat fluxes when strong shocks are present. Various efforts have been made to address the underlying numerical issues that cause the erroneous predictions. The present work addresses some of the shortcomings of unstructured grid solvers, not by addressing the numerics, but by applying structured grid best practices to unstructured grids. A methodology for robust shock detection and shock-fitting is outlined and applied to production-relevant cases. Results

McCoud, Peter L.↗

IFCPT S-Duct Grid-Adapted FUN3D Computations for the Third Propulsion Aerodynamics Works

Contributions of the unstructured Reynolds-averaged Navier-Stokes code, FUN3D, to the 3rd AIAA Propulsion Aerodynamics Workshop are described for the diffusing IFCPT S-Duct. Using workshop-supplied grids, results for the baseline S-Duct, baseline S-Duct with Aerodynamic Interface Plane (AIP) rake hardware, and baseline S-Duct with flow control devices are compared with experimental data and results computed with output-based, off-body grid adaptation in FUN3D. Due to the absence of influential geometry components, total pressure recovery is overpredicted on the baseline S-Duct and S-Duct with flow control vanes when compared to experimental values. An estimate for the exact value of total pressure recovery is derived for these cases given an infinitely refined mesh. When results from output-based mesh adaptation are compared with those computed on workshop-supplied grids, a considerable improvement in predicting total pressure recovery is observed. By including more representative geometry, output-based mesh adaptation compares very favorably with experimental data in terms of predicting the total pressure recovery cost-function; whereas, results computed using the workshop-supplied grids are underpredicted.

Davis, Zach S.↗

Sonora: A New Generation Model Atmosphere Grid for Brown Dwarfs and Young Extrasolar Giant Planets

Brown dwarf and giant planet atmospheric structure and composition has been studied both by forward models and, increasingly so, by retrieval methods. While indisputably informative, retrieval methods are of greatest value when judged in the context of grid model predictions. Meanwhile retrieval models can test the assumptions inherent in the forward modeling procedure. In order to provide a new, systematic survey of brown dwarf atmospheric structure, emergent spectra, and evolution, we have constructed a new grid of brown dwarf model atmospheres. We ultimately aim for our grid to span substantial ranges of atmospheric metallilcity, C/O ratios, cloud properties, atmospheric mixing, and other parameters. Spectra predicted by our modeling grid can be compared to both observations and retrieval results to aid in the interpretation and planning of future telescopic observations. We thus present Sonora, a new generation of substellar atmosphere models, appropriate for application to studies of L, T, and Y-type brown dwarfs and young extrasolar giant planets. The models describe the expected temperature-pressure profile and emergent spectra of an atmosphere in radiative-convective equilibrium for ranges of effective temperatures and gravities encompassing 200 less than or equal to T(sub eff) less than or equal to 2400 K and 2.5 less than or equal to log g less than or equal to 5.5. In our poster we briefly describe our modeling methodology, enumerate various updates since our group's previous models, and present our initial tranche of models for cloudless, solar metallicity, and solar carbon-to-oxygen ratio, chemical equilibrium atmospheres. These models will be available online and will be updated as opacities and cloud modeling methods continue to improve.

emergent spectra↗

High-Efficiency Food Production in a Renewable Energy Based Micro-Grid

Controlled Environment Agriculture (CEA) systems can be used to produce high-quality, desirable food year round, and the fresh produce can positively contribute to the health and well being of residents in communities with difficult supply logistics. While CEA has many positive outcomes for a remote community, the associated high electric demands have prohibited widespread implementation in what is typically already a fully subscribed power generation and distribution system. Recent advances in CEA technologies as well as renewable power generation, storage, and micro-grid management are increasing system efficiency and expanding the possibilities for enhancing community supporting infrastructure without increasing demands for outside supplied fuels. We will present examples of how new lighting, nutrient delivery, and energy management and control systems can enable significant increases in food production efficiency while maintaining high yields in CEA.Examples from Alaskan communities where initial incorporation of renewable power generation, energy storage and grid management techniques have already reduced diesel fuel consumption for electric generation by more than 40 and expanded grid capacity will be presented. We will discuss how renewable power generation, efficient grid management to extract maximum community service per kW, and novel energy storage approaches can expand the food production, water supply, waste treatment, sanitation and other community support services without traditional increases of consumable fuels supplied from outside the community. These capabilities offer communities with a range of choices to enhance their communities. The examples represent a synergy of technology advancement efforts to develop sustainable community support systems for future space-based human habitats and practical implementation of infrastructure components to increase efficiency and enhance health and well-being in remote communities today and tomorrow.

Renewable Energy↗

Assessing Uncertainties in Gridded Emissions: A Case Study for Fossil Fuel Carbon Dioxide (FFCO2) Emission Data

Fossil fuel carbon dioxide (CO2) emissions (FFCO2) are the largest input to the global carbon cycle on a decadal time scale. Because total emissions are assumed to be reasonably well constrained by fuel statistics, FFCO2 often serves as a reference in order to deduce carbon uptake by poorly understood terrestrial and ocean sinks. Conventional atmospheric CO2 flux inversions solve for spatially explicit regional sources and sinks and estimate land and ocean fluxes by subtracting FFCO2. Thus, errors in FFCO2 can propagate into the final inferred flux estimates. Gridded emissions are often based on disaggregation of emissions estimated at national or regional level. Although national and regional total FFCO2 are well known, gridded emission fields are subject to additional uncertainties due to the emission disaggregation. Assessing such uncertainties is often challenging because of the lack of physical measurements for evaluation. We first review difficulties in assessing uncertainties associated with gridded FFCO2 emission data and present several approaches for evaluation of such uncertainties at multiple scales. Given known limitations, inter-emission data differences are often used as a proxy for the uncertainty. The popular approach allows us to characterize differences in emissions, but does not allow us to fully quantify emission disaggregation biases. Our work aims to vicariously evaluate FFCO2 emission data using atmospheric models and measurements. We show a global simulation experiment where uncertainty estimates are propagated as an atmospheric tracer (uncertainty tracer) alongside CO2 in NASA's GEOS model and discuss implications of FFCO2 uncertainties in the context of flux inversions. We also demonstrate the use of high resolution urban CO2 simulations as a tool for objectively evaluating FFCO2 data over intense emission regions. Though this study focuses on FFCO2 emission data, the outcome of this study could also help improve the knowledge of similar gridded emissions data for non-CO2 compounds with similar emission characteristics.

FFCO↗

Geometrically Flexible and Efficient Flow Analysis of High Speed Vehicles Via Domain Decomposition, Part 1: Unstructured-Grid Solver for High Speed Flows

The ability to solve the equations governing the hypersonic turbulent flow of a real gas on unstructured grids using a spatially-elliptic, 2nd-order accurate, cell-centered, finite-volume method has been recently implemented in the VULCAN-CFD code. This paper describes the key numerical methods and techniques that were found to be required to robustly obtain accurate solutions to hypersonic flows on non-hex-dominant unstructured grids. The methods and techniques described include: an augmented stencil, weighted linear least squares, cell-average gradient method, a robust multidimensional cell-average gradient-limiter process that is consistent with the augmented stencil of the cell-average gradient method and a cell-face gradient method that contains a cell skewness sensitive damping term derived using hyperbolic diffusion based concepts. A data-parallel matrix-based symmetric Gauss-Seidel point-implicit scheme, used to solve the governing equations, is described and shown to be more robust and efficient than a matrix-free alternative. In addition, a y+ adaptive turbulent wall boundary condition methodology is presented. This boundary condition methodology is deigned to automatically switch between a solve-to-the-wall and a wall-matching-function boundary condition based on the local y+ of the 1st cell center off the wall. The aforementioned methods and techniques are then applied to a series of hypersonic and supersonic turbulent flat plate unit tests to examine the efficiency, robustness and convergence behavior of the implicit scheme and to determine the ability of the solve-to-the-wall and y+ adaptive turbulent wall boundary conditions to reproduce the turbulent law-of-the-wall. Finally, the thermally perfect, chemically frozen, Mach 7.8 turbulent flow of air through a scramjet flow-path is computed and compared with experimental data to demonstrate the robustness, accuracy and convergence behavior of the unstructured-grid solver for a realistic 3-D geometry on a non-hex-dominant grid.

White, Jeffery A.↗

Generalised Primal-Dual Grids for Unstructured Co-Volume Schemes

The generation of high-quality staggered unstructured grids is considered, leading to the development of a new optimisation-based strategy designed to construct weighted 'Regular-Power' tessellations appropriate for co-volume type numerical discretisation techniques. This new framework aims to extend the conventional Delaunay-Voronoi primal-dual structure; seeking to assemble generalised orthogonal tessellations with enhanced geometric quality. The construction of these grids is motivated by the desire to improve the performance and accuracy of numerical methods based on unstructured co-volume type schemes, including various staggered grid techniques for the simulation of fluid dynamics and hyperbolic transport. In this study, a new hybrid optimisation strategy is proposed; seeking to optimise the geometry, topology and weights associated with general, two-dimensional Regular-Power tessellations using a combination of gradient-ascent and energy-based techniques. The performance of this new method is tested experimentally, with a range of complex, multi-resolution primal-dual grids generated for various coastal and regional ocean modelling applications.

power diagrams↗

Evaluation of a Laser-Dot Grid-Projection System for Lunar Lander Crater-Shape and Ejecta-Sheet Measurements

Development, testing, and evaluation of an active-illumination laser-dot grid-projection system was performed to evaluate its potential inclusion on an upcoming uncrewed lunar lander mission to the south pole region of the moon. Active illumination may be required for this mission due to the shallow angle of the sun at the landing location, which may cast shadows in the landing region, hindering the stereo camera imaging system’s ability to determine the pre-and post-landing lunar surface/crater shape. Testing includes characterization of the diffractive optical elements used for the grid projection, single-camera tests to determine the imaged laser dot intensity as a function of camera exposure and imaging angle relative to the laser grid projection, laser dot brightness/saturation impact on depth map calculations, angle of imaged laser grid impact on depth map calculations for steep crater edges, impact of density gradients on the depth map calculations, and the feasibility of making measurements of the ejecta sheet.

Joshua M. Weisberger↗

Merged and Gridded GPM and Atmospheric River Data Product

The Global Precipitation Measurement (GPM) Mission Core Observatory satellite launched in 2014 as a joint mission between National Aeronautics and Space Administration (NASA) and JAXA. Global Precipitation Measurement (GPM) has, since that time, provided continuous, valuable dual-frequency radar and passive microwave radiometer observations. Here, we introduce a gridded data set of collocated GPM Core Observatory observational products merged with a reanalysis-derived Atmospheric river (AR) data set in the North Atlantic and North Pacific sectors. The three data sets that are merged and gridded are: (a) the NASA Goddard Profiling (GPROF) precipitation product, which uses GPM passive microwave radiometer observations to derive surface precipitation rates, (b) a water vapor data product derived from the GPM Core Observatory radiometer, provided by Remote Sensing Systems (RSS), and (c) the Mattingly et al. (2018, https://doi.org/10.1029/2018jd028714) AR data set that is specifically tuned to the high-latitude regions. This novel merged data set spans from May 2014 to December 2022 with plans to update annually through 2026 at minimum. This gridded product combines RSS passive water vapor and precipitation estimates with coincident AR detection. This data product benefits the scientific community by providing (a) user-friendly gridded satellite data compared to standard satellite data sets, while maintaining high temporal resolution, and (b) coincident satellite observations to assess the link between ARs and precipitation.

Marian E Mateling↗

An Approach for Practical Grid-Resolved Roughness Aerothermodynamic Simulations for Woven Heatshield Surfaces

An approach for simulating the aerothermal environment over a patterned roughness surface within an otherwise axisymmetric flow is developed. The patterned roughness is simplified into a sinusoidal shape that captures the basic features of a charred 3MDCP ablator. Two orientations of this pattern, which are equally flight relevant due to the forming process, enable periodic boundary conditions along the edges of a grid spanning a single roughness element. This simplified three-dimensional grid represents the minimum problem size for a patterned roughness simulation, which enables computationally efficient grid-resolved roughness simulations. This approach is validated by simulating the Langley Mach 6 measurements made on a similar sinusoidal surface, which results in convective heating within 5% of the experimental data. Applying this approach to Mars Sample Return (MSR) Earth Entry System (EES) flight cases, considering simulations with both 11 species air and 30 species air with ablation products, results in heating augmentation that is slightly lower than the widely-used Dahm correlation approach, with the difference being dependent on pattern orientation. This result provides the only insight into the behavior of the roughness augmentation at the high temperature reacting flow conditions present for EES flight cases, which are not captured by available ground test measurements. For shear augmentation, the simulations revealed that the surface-parallel pressure component is dominant. For arc-jet tests targeted to flight values for shear, the higher arc-jet pressures required to match flight values for shear result in up to a 400% increase in the rough wall shear value, which is not captured by the Dahm correlation. This indicates that, to avoid significant over-testing, grid-resolved roughness simulations are required to determine arc-jet conditions that produce flight shear levels in rough-wall scenarios.

Christopher O Johnston↗

Regional and Model-Specific Response Types in A Global Gridded Crop Model Ensemble

Crop models are often employed to project crop yields under changing conditions such as global warming and associated management change for adaptation. Multi-model ensembles are promoted to enhance the robustness of projections, but questions remain on what causes often large differences between projections of individual models. Global Gridded Crop Models (GGCMs) are especially exposed to this question when applied for assessing climate change impacts, adaptation, environmental impacts of agricultural production, because their results are used in downstream analyses, such as in integrated assessment or economic modeling for projecting future land-use change. Even though global gridded crop models are often based on detailed field-scale models or have implemented similar modeling principles in other ecosystem models, global-scale models are subject to substantial uncertainties from both model structure and parametrization as well as from calibration and input data quality. AgMIP’s Global Gridded Crop Model Intercomparison (GGCMI) has thus set out to intercompare GGCMs in order to evaluate model performance, describe model uncertainties, identify inconsistencies within the ensemble and underlying reasons, and to ultimately improve models and modeling capacities. In phase 2 of the GGCMI activities, 12 modeling groups followed a modeling protocol that asked for up to 1404 31-year global simulations at 0.5 arc-degree spatial resolution to assess models’ sensitivities to changes in carbon dioxide (C; 4 different levels) temperature (T; 7 different offset levels), water supply (W; 9 levels), and nitrogen (N; 3 levels), the so-called CTWN experiment (Franke et al. 2020; http://dx.doi.org/10.5194/gmd-13-2315-2020). We here present analyses of model response types using impact response surfaces along the C, T, W, and N dimensions, respectively and collectively. Doing so, we can understand differences in simulated responses per driver rather than aggregated changes in yields. We find that models’ sensitivities to the individual driver dimensions are substantially different and often more different across models than across regions. A cluster analysis finds regional and model-specific patterns. There is some agreement across models with respect to the spatial patterns of response types but strong differences in the distribution of response type clusters across models suggests that models need to undergo further scrutiny. We suggest establishing standards in model process evaluation not only against historical dynamics but also against dedicated experiments across the CTWN dimensions.

crop models↗

Test-to-Failure of a Two-Grid, 30-cm-dia. Ion Accelerator System

To determine the failure mechanism and erosion characteristics of an ion accelerator system due to erosion by charge-exchange ions a test was performed in which a 30-cm-diameter, 2-grid ion accelerator system was tested to failure. The erosion charcteristics observed in this test, however, imply significantly shorter accelerator grid life times than typically stated in the literature. Finally, the test suggests that structural failure is probably not the most likely first failure mechanism for the accelerator grid.

distortion↗

GLIDE: a grid-based light-weight infrastructure for data-intensive environments

The promise of the grid is that it will enable public access and sharing of immense amounts of computational and data resources among dynamic coalitions of individuals and institutions. However, the current grid solutions make several limiting assumptions that curtail their widespread adoption. To address these limitations, we present GLIDE, a prototype light-weight, data-intensive middleware infrastructure that enables access to the robust data and computational power of the grid on DREAM platforms.

PRISM-MW↗

Variable High Order Multiblock Overlapping Grid Methods for Mixed Steady and Unsteady Multiscale Viscous Flows

Flows containing steady or nearly steady strong shocks in parts of the flow field, and unsteady turbulence with shocklets on other parts of the flow field are difficult to capture accurately and efficiently employing the same numerical scheme even under the multiblock grid or adaptive grid refinement framework. On one hand, sixth-order or higher shock-capturing methods are appropriate for unsteady turbulence with shocklets. On the other hand, lower order shock-capturing methods are more effective for strong steady shocks in terms of convergence. In order to minimize the shortcomings of low order and high order shock-capturing schemes for the subject flows,a multi- block overlapping grid with different orders of accuracy on different blocks is proposed. Test cases to illustrate the performance of the new solver are included.

Multiscale viscous flows↗

Spatial Grid-Based Object Localization from A Single Passive Sensor: A Deep Learning-Integrated Approach

Ongoing efforts at NASA’s Langley Research Center have produced a single passive sensor system for detecting ground objects and pinpointing their real-world location to a desired level of precision. The Langley center serves as a test range for unmanned aerial systems (UAS) and real-time knowledge about the location of people on campus is needed to inform least-risk UAS flight operations. The proposed system provides this knowledge through a camera combined with a convolutional neural network and an algorithm that projects an imaginary grid of square cells from the ground plane onto the perspective view of the camera. The position of detected objects on the camera’s projected grid determines their location in the real-world. The imaginary grid is easily mapped to a universal coordinate system, such as longitude and latitude, to provide both relative and absolute positional information of the detected objects. This simple system is shown to be accurate and effective, with decisive advantages over alternative multi-sensor and active sensor approaches. Extensions to the system are described to allow adaptation to a variety of other use cases.

object localization↗

Extending an Economical Third-Order Inviscid Nodal-Gradient Cell-Centered Finite-Volume Method to Mixed-Element Grids

In this paper, we extend an economical third-order nodal-gradient cell-centered finite-volume method, originally developed for tetrahedral grids, to mixed-element grids. It is shown that the efficient quadratic interpolation formula essential to eliminating second derivatives from a third-order accurate discretization can be easily extended to an arbitrary cell type. For the surface flux integration, we consider a split-face approach, where a quadrilateral face is split into two triangles, and the third-order method for tetrahedra is directly applied. Also, we derive a second-derivative-free, high-order, volume quadrature formula for an arbitrary cell. Numerical results are presented for accuracy verification and applications with three-dimensional nontetrahedral grids.

Computational Fluid Dynamics↗