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At least 1,171 records · Page 65

Uncertain Spatial Pattern of Future Land Use and Land Cover Change and Its Impacts on Terrestrial Carbon Cycle Over the Arctic–Boreal Region of North America

Land use and land cover change (LULCC) represents a key process of human-Earth system interaction and has profound impacts on terrestrial ecosystem carbon cycling. As a key input for ecosystem models, future gridded LULCC data is typically spatially downscaled from regional LULCC projections by integrated assessment models, such as the Global Change Analysis Model (GCAM). The uncertainty associated with the different spatial downscaling methods and its impacts on the subsequent model projections have been historically ignored and rarely examined. This study investigated this problem using two representative spatial downscaling methods and focused on their impacts on the carbon cycle over the Arctic-Boreal Vulnerability Experiment (ABoVE) domain, where extensive LULCC is expected. Specifically, we used the Future Land Use Simulation model (FLUS) and the Demeter model to generate 0.25° gridded LULCC data (i.e., LULCC FLUS and LULCC Demeter , respectively) with the same input of regional LULCC projections from GCAM, under both the low (i.e., SSP126) and high (i.e., SSP585) greenhouse gas emission scenarios. The two sets of downscaled LULCC were used to drive the Community Land Model version 5 and prognostically simulate the terrestrial carbon cycle dynamics over the 21st century. The results suggest large spatial-temporal differences between LULCC FLUS and LULCC Demeter , and the spatial distributions of the needleleaf evergreen boreal tree, broadleaf deciduous boreal tree, broadleaf deciduous boreal shrub, and C3 arctic grass are particularly different under both SSP126 and SSP585. Additionally, the spatiotemporal differences are larger under SSP126 than SSP585, due to more intensive LULCC under SSP126 than SSP585 from GCAM projection. The differences in LULCC further lead to large discrepancies in the spatial patterns of projected gross primary productivity, ecosystem respiration, and net ecosystem exchange, which represent more than 79% of the contributions of future LULCC in 2100. Additionally, the difference in carbon flux under SSP126 is generally larger than those under SSP585. This study highlights the importance of considering the uncertainties induced by the spatial downscaling process in future LULCC projections and carbon cycle simulations.

54 ENVIRONMENTAL SCIENCES↗

Airfoil Computational Fluid Dynamics - 2k shapes, 25 AoA's, 3 Re numbers

This dataset contains aerodynamic quantities - including flow field values (momentum, energy, and vorticity) and summary values (coefficients of lift, drag, and momentum) - for 1,830 airfoil shapes computed using the HAM2D CFD (computational fluid dynamics) model. The airfoil shapes were designed using the separable shape tensor parameterization that encodes two-dimensional shapes as elements of the Grassmann manifold. This data-driven approach learns two independent spaces of parameter from a collection of sample airfoils. The first captures large-scale, linear perturbations, and the second defines small-scale, higher-order perturbations. For this dataset, we used the G2Aero database of over 19,000 airfoil shapes to learn a parameter space that captured a wide array of shape characteristics. We sampled airfoil designs over both parameter spaces to explore the full range of possible shape variations. The aerodynamic quantities for the generated airfoil were obtained using the HAM2D code, which is a finite-volume Reynolds-averaged Navier-Stokes (RANS) flow solver. We employ a fifth-order WENO scheme for spatial reconstruction with Roe's flux difference scheme for inviscid flux and second-order central differencing for viscous flux. A preconditioned GMRES method is applied for implicit integration. The Spalart-Allmaras 1-eq turbulence model is used for the turbulence closure, and the Medida-Baeder 2-eq transition model is applied to account for the effects of laminar turbulent transition. The airfoil grid is generated with a total of 400 points on the airfoil surface, the initial wall-normal spacing of y+ = 1, and an outer boundary located at 300 chord lengths away from the wall. The CFD simulations are performed at a freestream Mach number of 0.1, for or three different Reynolds' numbers (3M, 6M, and 9M), and for 25 angles of attack from -4 deg. to 20 deg. with 1 degree increments. Across all these various parameters, this dataset includes the results from over 250,000 CFD simulations. The simulations were performed using the Bridges-2 system at the Pittsburgh Supercomputing Center in February 2023 as part of the INTEGRATE project funded by the Advanced Research Projects Agency - Energy, in the U.S. Department of Energy. The data was collected, reformatted, and preprocessed for this OEDI submission in July 2023 under the Foundational AI for Wind Energy project funded by the U.S. Department of Energy Wind Energy Technologies Office. This dataset is intended to serve as a benchmark against which new artificial intelligence (AI) or machine learning (ML) tools may be tested. Baseline AI/ML methods for analyzing this dataset have been implemented, and a link to their repository containing those models has been provided. The .h5 data file structure can be found in the GitHub Repository resource under explore_airfoil_2k_data.ipynb.

2k↗

Airfoil Computational Fluid Dynamics - 9k shapes, 2 AoA's

This dataset contains aerodynamic quantities - including flow field values (momentum, energy, and vorticity) and summary values (coefficients of lift, drag, and momentum) - for 8,996 airfoil shapes, computed using the HAM2D CFD (computational fluid dynamics) model. The airfoil shapes were designed using the separable shape tensor parameterization that encodes two-dimensional shapes as elements of the Grassmann manifold. This data-driven approach learns two independent spaces of parameter from a collection of sample airfoils. The first captures large-scale, linear perturbations, and the second defines small-scale, higher-order perturbations. For this data, we used the G2Aero database of over 19,000 airfoil shapes to learn a parameter space that captured a wide array of shape characteristics. We fixed the linear deformations to be the mean over the database and sampled new shapes over a four-dimensional parameter space of higher-order perturbation. This sampling approaches allows for isolated analysis of non-linear airfoil shape deformations while holding other aspects (e.g., airfoil thickness) approximately constant. The aerodynamic quantities for the generated airfoil were obtained using the HAM2D code, which is a finite-volume Reynolds-averaged Navier-Stokes (RANS) flow solver. We employ a fifth-order WENO scheme for spatial reconstruction with Roe's flux difference scheme for inviscid flux and second-order central differencing for viscous flux. A preconditioned GMRES method is applied for implicit integration. The Spalart-Allmaras 1-eq turbulence model is used for the turbulence closure, and the Medida-Baeder 2-eq transition model is applied to account for the effects of laminar turbulent transition. The airfoil grid is generated with a total of 400 points on the airfoil surface, the initial wall-normal spacing of y+ = 1, and an outer boundary located at 300 chord lengths away from the wall. The CFD simulations are performed at a freestream Mach number of 0.1, Reynolds number of 9M, and at two angles of attack, 4 deg. and 12 deg. The simulations were performed using the Bridges-2 system at the Pittsburgh Supercomputing Center in February 2023 as part of the INTEGRATE project funded by the Advanced Research Projects Agency - Energy in the U.S. Department of Energy. The data was collected, reformatted, and preprocessed for this OEDI submission in July 2023 under the Foundational AI for Wind Energy project funded by the U.S. Department of Energy Wind Energy Technologies Office. This dataset is intended to serve as a benchmark against which new artificial intelligence (AI) or machine learning (ML) tools may be tested. Baseline AI/ML methods for analyzing this dataset have been implemented, and a link to their repository containing those models has been provided. The .h5 data file structure can be found in the GitHub Repository resource under explore_airfoil_9k_data.ipynb.

9k↗

THE HERSCHEL ORION PROTOSTAR SURVEY: SPECTRAL ENERGY DISTRIBUTIONS AND FITS USING A GRID OF PROTOSTELLAR MODELS

We present key results from the Herschel Orion Protostar Survey: spectral energy distributions (SEDs) and model fits of 330 young stellar objects, predominantly protostars, in the Orion molecular clouds. This is the largest sample of protostars studied in a single, nearby star formation complex. With near-infrared photometry from 2MASS, mid- and far-infrared data from Spitzer and Herschel , and submillimeter photometry from APEX, our SEDs cover 1.2–870 μ m and sample the peak of the protostellar envelope emission at ∼100 μ m. Using mid-IR spectral indices and bolometric temperatures, we classify our sample into 92 Class 0 protostars, 125 Class I protostars, 102 flat-spectrum sources, and 11 Class II pre-main-sequence stars. We implement a simple protostellar model (including a disk in an infalling envelope with outflow cavities) to generate a grid of 30,400 model SEDs and use it to determine the best-fit model parameters for each protostar. We argue that far-IR data are essential for accurate constraints on protostellar envelope properties. We find that most protostars, and in particular the flat-spectrum sources, are well fit. The median envelope density and median inclination angle decrease from Class 0 to Class I to flat-spectrum protostars, despite the broad range in best-fit parameters in each of the three categories. We also discuss degeneracies in our model parameters. Our results confirm that the different protostellar classes generally correspond to an evolutionary sequence with a decreasing envelope infall rate, but the inclination angle also plays a role in the appearance, and thus interpretation, of the SEDs.

79 ASTRONOMY AND ASTROPHYSICS↗

Data-Driven Unit Commitment Refinement - a Scalable Approach for Complex Modern Power Grids

Integration of renewable generation, which is often intermittent and decentralized, substantially increases the stochasticity and complexity of power grid operations. Future power systems planning will require significant computational capability to evaluate balance between demand and supply under varying conditions, both temporally and spatially. The standard approach for generation unit commitment is to use mixed-integer linear programming to find the optimal generation schedule considering ramping and generator constraints. In the future grid this poses computational scalability challenges because generation and demand are not known with certainty due to stochasticity in weather and complexity of the grid. To address this challenge, we present a data-driven unit commitment approach that can efficiently include stochastic weather impacts and contingency considerations to improve unit commitment. Our approach uses graph-based data analytics techniques on solutions to the security constrained (and possibly stochastic) economic dispatch problem to identify potential improvements to a given unit commitment. Recent breakthroughs in fully-parallel stochastic economic dispatch software allow this approach to be scalably deployed. Simulations on synthetic South Carolina and Texas grids show this method can improve grid reliability with security constraints over a set of contingencies, while also meaningfully lowering total generation cost.

Holt, Timothy↗

The Illumination of Thunderclouds by Lightning: 2. The Effect of GLM Instrument Threshold on Detection and Clustering

Abstract Lightning is measured from space using optical instruments that detect transient changes in the illumination of the cloud top. How much of the flash (if any) is recorded by the instrument depends on the instrument detection threshold. NOAA's Geostationary Lightning Mapper (GLM) employs a dynamic threshold that varies across the imaging array and changes over time. This causes flashes in certain regions and at night to be recorded in greater detail than other flashes, and threshold inconsistencies will impose biases on all levels of GLM data products. In this study, we quantify the impact of the varying GLM threshold on event/group/flash detection, flash clustering, and gridded product generation by imposing artificial thresholds on the event data taken from a thunderstorm with a low instrument threshold (∼0.7 fJ). We find that even modest increases in threshold severely impact event (60% loss by 2 fJ, 90% loss by 10 fJ) and group (25% loss by 2 fJ, 81% loss by 10 fJ) detection by suppressing faint illumination of the cloud top from weak sources and scattering. Flash detection is impacted less by threshold increases (4% loss by 2 fJ), but reductions are still significant at higher thresholds (35% loss by 10 fJ, or 44% if single‐group flashes are removed). Undetected pulses cause individual flashes to be split and severely impact the construction of gridded products. All of these factors complicate the interpretation of GLM data, particularly when trended over time under a changing threshold.

54 ENVIRONMENTAL SCIENCES↗

A procedure for automating CFD simulations of an inlet-bleed problem

A procedure was developed to improve the turn-around time for computational fluid dynamics (CFD) simulations of an inlet-bleed problem involving oblique shock-wave/boundary-layer interactions on a flat plate with bleed into a plenum through one or more circular holes. This procedure is embodied in a preprocessor called AUTOMAT. With AUTOMAT, once data for the geometry and flow conditions have been specified (either interactively or via a namelist), it will automatically generate all input files needed to perform a three-dimensional Navier-Stokes simulation of the prescribed inlet-bleed problem by using the PEGASUS and OVERFLOW codes. The input files automatically generated by AUTOMAT include those for the grid system and those for the initial and boundary conditions. The grid systems automatically generated by AUTOMAT are multi-block structured grids of the overlapping type. Results obtained by using AUTOMAT are presented to illustrate its capability.

Chyu, Wei J.↗

Influences of North Pacific Ocean Domain Extent on the Western U.S. Winter Hydroclimatology in Variable-Resolution CESM

Variable-resolution global climate models (VRGCMs) are a dynamical downscaling method that can reach spatiotemporal scales needed for regional climate assessments. Over the years, several users of VRGCMs have assumed where the location and extent of the refinement domain should be based on knowledge of the prevailing storm tracks and resolution dependence of important regional climate processes (e.g., atmospheric rivers [ARs] and orographic uplift), but the effect of high-resolution domain size and extent on the simulation of downstream hydroclimatic phenomena has not been systematically evaluated. Here, we use variable resolution in the Community Earth System Model (VR-CESM) to perform such a test. To do this, three VR-CESM grids were generated that span the entire, two thirds, and one third of the North Pacific and evaluated for a 30-year climatology using Atmospheric Model Intercomparison Project protocols. Simulations are compared with reanalysis products offshore (fifth-generation of the European Centre for Medium-Range Weather Forecasts atmospheric reanalysis [ERA5]) and onshore (Livneh, 2015, https://doi.org/10.1038/sdata.2015.42, and Parameter-elevation Regressions on Independent Slopes Model [PRISM]) of the western United States. The westward expansion of refinement domain influenced integrated vapor transport (IVT), which was generally high biased but minimally impacted AR characteristics. Due to slight differences in landfalling AR counts in the western United States, California winter precipitation generally improved with westward expansion of the refinement domain. Western U.S. mountain snowpack and surface temperatures were insensitive to refinement domain size and were more influenced by changes in topographic resolution and/or land surface model version. Here, given minimal dependence of simulated western U.S. hydroclimate on refinement domain size over the North Pacific, we advise future VR-CESM studies to focus grid resolution on better resolving land surface heterogeneity.

54 ENVIRONMENTAL SCIENCES↗

Sonic Boom Prediction and Minimization of the Douglas Reference OPT5 Configuration

Conventional CFD methods and grids do not yield adequate resolution of the complex shock flow pattern generated by a real aircraft geometry. As a result, a unique grid topology and supersonic flow solver was developed at Northrop Grumman based on the characteristic behavior of supersonic wave patterns emanating from the aircraft. Using this approach, it was possible to compute flow fields with adequate resolution several body lengths below the aircraft. In this region, three-dimensional effects are diminished and conventional two-dimensional modified linear theory (MLT) can be applied to estimate ground pressure signatures or sonic booms. To accommodate real aircraft geometries and alleviate the burdensome grid generation task, an implicit marching multi-block, multi-grid finite-volume Euler code was developed as the basis for the sonic boom prediction methodology. The Thomas two-dimensional extrapolation method is built into the Euler code so that ground signatures can be obtained quickly and efficiently with minimum computational effort suitable to the aircraft design environment. The loudness levels of these signatures can then be determined using a NASA generated noise code. Since the Euler code is a three-dimensional flow field solver, the complete circumferential region below the aircraft is computed. The extrapolation of all this field data from a cylinder of constant radius leads to the definition of the entire boom corridor occurring directly below and off to the side of the aircraft's flight path yielding an estimate for the entire noise "annoyance" corridor in miles as well as its magnitude. An automated multidisciplinary sonic boom design optimization software system was developed during the latter part of HSR Phase 1. Using this system, it was found that sonic boom signatures could be reduced through optimization of a variety of geometric aircraft parameters. This system uses a gradient based nonlinear optimizer as the driver in conjunction with a computationally efficient Euler CFD solver (NIIM3DSB) for computing the three-dimensional near-field characteristics of the aircraft. The intent of the design system is to identify and optimize geometric design variables that have a beneficial impact on the ground sonic boom. The system uses a simple wave drag data format to specify the aircraft geometry. The geometry is internally enhanced and analytic methods are used to generate marching grids suitable for the multi-block Euler solver. The Thomas extrapolation method is integrated into this system, and hence, the aircraft's centerline ground sonic boom signature is also automatically computed for a specified cruise altitude and yields the parameters necessary to evaluate the design function. The entire design system has been automated since the gradient based optimization software requires many flow analyses in order to obtain the required sensitivity derivatives for each design variable in order to converge on an optimal solution. Hence, once the problem is defined which includes defining the objective function and geometric and aerodynamic constraints, the system will automatically regenerate the perturbed geometry, the necessary grids, the Euler solution, and finally the ground sonic boom signature at the request of the optimizer.

Siclari, Michael J.↗

Lower Snake River Dams Contribution to Grid Services

Hydroelectric generation and water storage have long been components of the clean energy mix, providing both reliable steady output and operational flexibility. As variable renewable energy sources such as wind and solar increasingly replace traditional generation, the role of all flexible resources—including hydropower—in balancing supply and demand continues to evolve. This study examined the contribution of the Lower Snake River (LSR) Dam plants to Bonneville Power Administration grid services in maintaining power system reliability within the Western Interconnection. By analyzing publicly available data, the study evaluated various reliability services through performance metrics including energy capacity, balancing and ramping, voltage and reactive power support, frequency response, and transmission impact. Results indicated that the LSR plants deliver services as expected based on their size, contributing to the balancing process, ramping capabilities, and operational reserves, particularly during peak load conditions and weather events, while also providing measurable frequency and voltage support to the grid.

13 HYDRO ENERGY↗

Will Solar Panels Help When the Power Goes Out? Planning for PV Resilience

PV systems, like all energy systems, must chart a difficult course in order to improve resilience. They need to simultaneously withstand extreme conditions that cause grid power disruptions, be configured in a way that allows electricity to be delivered to meet the PV user's needs, and overcome disruptions arising from solar resource intermittency. Certain considerations reveal themselves as key to a PV system's resilience benefits. Choice of hardware is critical, as is site selection for the PV array. Voluminous evidence in a hurricane context demonstrates that durable hardware, properly maintained and sited, leads to PV systems surviving extreme weather with their functionality intact. Structurally weak or poorly maintained PV equipment, on the other hand, has demonstrated failures during extreme weather events. PV system stakeholders should ensure that best practices are followed for hardware procurement and siting. It is also important to understand that PV systems are not one-size-fits-all. While incorporating islanding capabilities and energy storage into the system's electrical topology will typically enhance resilience, the user's needs will determine the optimally resilient conformation of any given system. These factors - appropriate hardware, siting, maintenance, and system design - are the primary drivers of PV resilience. PV systems possess high potential for resilient energy generation due to their distributed, abundant, and free fuel supply, but the technology itself does not inherently lead to resilient outcomes. Realizing PV's potential for resilience requires consideration of these determinative factors.

14 SOLAR ENERGY↗

Voronoi-Based Point-Placement for Three-Dimensional Delaunay-Refinement

An extension of the restricted Delaunay-refinement algorithm for three-dimensional tetrahedral mesh generation is described, in which an off-centre type point-placement scheme is utilised. It is shown that the use of generalised Steiner points, positioned along edges in the associated Voronoi complex, typically leads to improvements in the overall size, quality and grading of the resulting tetrahedral meshes. The new algorithm can be viewed as a Frontal-Delaunay approach - a hybridisation of conventional Delaunay-refinement and advancing-front techniques, in which new vertices are positioned to satisfy both element size- and shapeconstraints. The new method is shown to inherit many of the best features of classical Delaunay-refinement and advancing-front type algorithms, combining good practical performance with theoretical robustness. Experimental comparisons show that

algorithms↗

Mississippi State University Cooling, Heating, and Power (Micro-CHP) and Bio-Fuel Center

Between 2008 and 2014, the U.S. Department of Energy funded the MSU Micro-CHP and Bio-Fuel Center located at Mississippi State University. The overall objective of this project was to enable micro-CHP (micro-combined heat and power) utilization, to facilitate and promote the use of CHP systems and to educate architects, engineers, and agricultural producers and scientists on the benefits of CHP systems. Therefore, the work of the Center focused on the three areas: CHP system modeling and optimization, outreach, and research. In general, the results obtained from this project demonstrated that CHP systems are attractive because they can provide energy, environmental, and economic benefits. Some of these benefits include the potential to reduce operational cost, carbon dioxide emissions, primary energy consumption, and power reliability during electric grid disruptions. The knowledge disseminated in numerous journal and conference papers from the outcomes of this project is beneficial to engineers, architects, agricultural producers, scientists and the public in general who are interested in CHP technology and applications. In addition, more than 48 graduate students and 23 undergraduate students, benefited from the training and research performed in the MSU Micro-CHP and Bio-Fuel Center. The project scope consisted of six separate, but related areas: 1. Micro-CHP modeling - Computational simulations and verification/validation studies of selected models for technical and economic viability. 2. Fuel flexibility in micro-CHP applications – Demonstrating and quantifying the operation of micro-CHP systems on alternative fuels. 3. Outreach activities – Providing provide educational materials for engineers and architects and conducting outreach seminars, workshops, and demonstrations for engineers and architects as well as for more general audiences. 4. Biofuel and opportunity fuel processing and utilization – Determining the processing requirements and feasibility to utilize biofuels and disaster debris for micro-CHP systems. 5. CHP Systems Optimization – Optimization of internal combustion and Stirling engines integrated with heat recovery systems for CHP operation. 6. Distributed Generation and Grid Interconnection – Developing requirements and control systems for interconnection of micro-CHP systems with the electrical grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A critical assessment of stellar mass measurement methods

This is the second paper in a series aimed at investigating the main sources of uncertainty in measuring the observable parameters in galaxies from their spectral energy distributions (SEDs). In the first paper we presented a detailed account of the photometric redshift measurements and an error analysis of this process. In this paper we perform a comprehensive study of the main sources of random and systematic error in stellar mass estimates for galaxies, and their relative contributions to the associated error budget. Since there is no prior knowledge of the stellar mass of galaxies (unlike their photometric redshifts), we use mock galaxy catalogs with simulated multi-waveband photometry and known redshift, stellar mass, age and extinction for individual galaxies. The multi-waveband photometry for the simulated galaxies were generated in 13 filters spanning from U-band to mid-infrared wavelengths. Given different parameters affecting stellar mass measurement (photometric signal-to-noise ratios (S/N), SED fitting errors and systematic effects), the inherent degeneracies and correlated errors, we formulated different simulated galaxy catalogs to quantify these effects individually. For comparison, we also generated catalogs based on observed photometric data of real galaxies in the Great Observatories Origins Deep Survey-South field, spanning the same passbands. The simulated and observed catalogs were provided to a number of teams within the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey collaboration to estimate the stellar masses for individual galaxies. A total of 11 teams participated, with different combinations of stellar mass measurement codes/methods, population synthesis models, star formation histories, extinction and age. For each simulated galaxy, the differences between the input stellar masses, M{sub input}, and those estimated by each team, M{sub est}, is defined as Δlog(M)≡log(M{sub estimated})−log(M{sub input}), and used to identify the most fundamental parameters affecting stellar mass estimate in galaxies, with the following results. (1) No significant bias in Δ log(M) was found among different codes, with all having comparable scatter (σ(Δlog(M))=0.136 dex). The estimated stellar mass values are seriously affected by low photometric S/N, with the rms scatter increasing for galaxies with H{sub AB}>26 mag; (2) A source of error contributing to the scatter in Δ log(M) is found to be due to photometric uncertainties (0.136 dex) and low resolution in age and extinction grids when generating the SED templates; (3) The median of stellar masses among different methods provides a stable measure of the mass associated with any given galaxy (σ(Δlog(M))=0.142 dex); (4) The Δ log(M) values are strongly correlated with deviations in age (defined as the difference between the estimated and expected values), with a weaker correlation with extinction; (5) The rms scatter in the estimated stellar masses due to free parameters (after fixing redshifts and initial mass function) are quantified and found to be σ(Δlog(M))=0.110 dex; (6) Using the observed data, we studied the sensitivity of stellar masses to both the population synthesis codes and inclusion of nebular emission lines and found them to affect the stellar mass by 0.2 and 0.3 dex respectively.

79 ASTRONOMY AND ASTROPHYSICS↗

ICEG2D (v2.0) - An Integrated Software Package for Automated Prediction of Flow Fields for Single-Element Airfoils With Ice Accretion

An integrated geometry/grid/simulation software package, ICEG2D, is being developed to automate computational fluid dynamics (CFD) simulations for single- and multi-element airfoils with ice accretions. The current version, ICEG213 (v2.0), was designed to automatically perform four primary functions: (1) generate a grid-ready surface definition based on the geometrical characteristics of the iced airfoil surface, (2) generate high-quality structured and generalized grids starting from a defined surface definition, (3) generate the input and restart files needed to run the structured grid CFD solver NPARC or the generalized grid CFD solver HYBFL2D, and (4) using the flow solutions, generate solution-adaptive grids. ICEG2D (v2.0) can be operated in either a batch mode using a script file or in an interactive mode by entering directives from a command line within a Unix shell. This report summarizes activities completed in the first two years of a three-year research and development program to address automation issues related to CFD simulations for airfoils with ice accretions. As well as describing the technology employed in the software, this document serves as a users manual providing installation and operating instructions. An evaluation of the software is also presented.

Thompson David S.↗

Ionospheric calibration for single frequency altimeter measurements

This study is a preliminary analysis of the effectiveness (in terms of altimeter calibration accuracy) of various ionosphere models and the Global Positioning System (GPS) to calibrate single frequency altimeter height measurements for ionospheric path delay. In particular, the research focused on ingesting GPS Total Electron Content (TEC) data into the physical Parameterized Real-Time Ionospheric Specification Model (PRISM), which estimates the composition of the ionosphere using independent empirical and physical models and has the capability of adjusting to additional ionospheric measurements. Two types of GPS data were used to adjust the PRISM model: GPS receiver station data mapped from line-of-sight observations to the vertical at the point of interest and a grid map (generated at the Jet Propulsion Laboratory) of GPS derived TEC in a sun-fixed longitude frame. The adjusted PRISM TEC values, as well as predictions by the International Reference Ionosphere (IRI-90), a climatological (monthly mean) model of the ionosphere, were compared to TOPEX dual-frequency TEC measurements (considered as truth) for a number of TOPEX sub-satellite tracks. For a 13.6 GHz altimeter, a Total Electron Content (TEC) of 1 TECU 10(exp 16) electrons/sq m corresponds to approximately 0.218 centimeters of range delay. A maximum expected TEC (at solar maximum or during solar storms) of 10(exp 18) electrons/sq m will create 22 centimeters of range delay. Compared with the TOPEX data, the PRISM predictions were generally accurate within the TECU when the sub-satellite track of interest passed within 300 to 400 km of the GPS TEC data or when the track passed through a night-time ionosphere. If neither was the case, in particular if the track passed through a local noon ionosphere, the PRISM values differed by more than 10 TECU and by as much as 40 TECU. The IRI-90 model, with no current ability to unseat GPS data, predicted TEC to a slightly higher error of 12 TECU. The performance of PRISM is very promising for predicting TEC and will prove useful for calibrating single frequency altimeter height measurements for ionospheric path delay. When adjusted to the GPS line-of-sight data the PRISM URSI empirical model predicted TEC over a day's period to within a global error of 8.60 TECU rms during a nighttime ionosphere and 9.74 TECU rms during the day. When adjusted to the GPS derived TEC grid, the PRISM parametrized model predicted TEC to within an error of 8.47 TECU rms for a nighttime ionosphere and 12.83 TECU rms during the day. However, the grid cannot be considered globally due to the lack of sufficient numbers of GPS stations and large latitude gaps in GPS data. It is the opinion of the authors that using the PRISM model and adjusting to the global sun-fixed TEC grid regenerated with a localized weighted interpolation offers the best possibility of meeting the 10 TECU global rms (or 2 cm at 13.6 GHz) ionosphere range correction accuracy requirement of TOPEX/Poseidon and should be the subject of further study. However, it is clear that the anticipated requirement of 34 TECU global rms for TOPEX/Poseidon Follow-On (corresponding to the TOPEX/Poseidon performance) can not be met with any realizable combination of existing models and data assimilation schemes.

Schreiner, William S.↗

Adaptive unstructured triangular mesh generation and flow solvers for the Navier-Stokes equations at high Reynolds number

A method for generating high quality unstructured triangular grids for high Reynolds number Navier-Stokes calculations about complex geometries is described. Careful attention is paid in the mesh generation process to resolving efficiently the disparate length scales which arise in these flows. First the surface mesh is constructed in a way which ensures that the geometry is faithfully represented. The volume mesh generation then proceeds in two phases thus allowing the viscous and inviscid regions of the flow to be meshed optimally. A solution-adaptive remeshing procedure which allows the mesh to adapt itself to flow features is also described. The procedure for tracking wakes and refinement criteria appropriate for shock detection are described. Although at present it has only been implemented in two dimensions, the grid generation process has been designed with the extension to three dimensions in mind. An implicit, higher-order, upwind method is also presented for computing compressible turbulent flows on these meshes. Two recently developed one-equation turbulence models have been implemented to simulate the effects of the fluid turbulence. Results for flow about a RAE 2822 airfoil and a Douglas three-element airfoil are presented which clearly show the improved resolution obtainable.

Ashford, Gregory A.↗

Simulation of lithium transport using the BOUT++ framework

A numerical model that calculates the collisional interactions between the lithium atoms from a lithium pellet and the background plasmas has been upgraded. The ion density ($N_t$), electron temperature ($T_e$), ion temperature ($T_i$) and parallel ion velocity ($V_{∥, i}$) are used to characterize the background plasmas. The lithium atom density ($N^{a}_{Li}$) and parallel velocity ($V_{∥,a}$) of lithium atoms evolve with time. For each lithium ion, the density ($N_{Li^{n+}}$), temperature ($T_{Li^{n+}}$) and parallel velocity ($V_{∥, Li^{n+}}$) are self-consistently calculated. A C-mod lower single null equilibrium is used to generate the grid for the BOUT++ simulation. The lithium atoms can be fully ionized to $Li^{3+}$ in ~2 μs. The rapid radial and poloidal expansion of the lithium ions are found in the simulation. After the collision interaction process, the electron temperature rapidly decreases at the pellet location; then, it rapidly poloidally expands, and the temperature at the pellet location starts to recover. The electron pressure increases at the pellet location despite the decrease in electron temperature because of the extra electrons from the lithium ionization. The ion pressure profile decreases in the pellet location due to the decrease in ion temperature.

74 ATOMIC AND MOLECULAR PHYSICS↗