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At least 559 records · Page 31

Quantifying the Solar Energy Resource for Puerto Rico

After Hurricane Maria, multiple U.S. Department of Energy laboratories studied the state of the electric grid in Puerto Rico and analyzed grid resilience and grid integration of renewable energy. As part of the work done at the National Renewable Energy Laboratory, researchers created new solar resource data, conducted a technical potential and supply curve analysis, and studied the interannual variability of the solar resource. A new methodology was developed to downscale solar resource data from the National Solar Radiation Data Base (NSRDB) from a 4-km x 4-km spatial and 30-minute temporal resolution to a 2 km x 2 km and 5-minute resolution. This methodology primarily used simple physical principles to develop high-resolution cloud properties which were then used to compute solar radiation. The high-resolution datasets were validated against ground measurements and the error metrics were found to be similar to the original lower resolution dataset. Using 20 years of downscaled data from the NSRDB multi-year capacity factors for photovoltaics (PV) were developed for both single-axis tracking and fixed latitude-tilt configurations. Use of the multi-year data provides the ability to understand variability in capacity factors due to variability in weather over a long period of time. For Puerto Rico the coastal regions were found to have significant higher capacity factors than inland. Using land-use and terrain information a technical potential analysis was conducted for Puerto Rico. This analysis restricted single PV plant development to a maximum of 100 MW nameplate capacity. The nameplate capacity for each municipality were then determined. Based on our assumptions, 56 of the 78 total municipalities of Puerto Rico contain some level of solar capacity. Most of the interior municipalities did not have any capacity because of the geographic exclusions used in this study. The lowest capacity for a PV plant observed in a municipality was 10 MW. The maximum capacity within a county was 2,000 MW. Further a supply curve analysis was conducted by taking the results of the technical potential and quantifying system and transmission costs. The levelized cost of energy (LCOE) was calculated for each theoretical PV plant site, and the levelized cost of transmission was added to the LCOE to produce a total cost estimate for each site. The results of the supply curve analysis allow for a relative comparison of the cost for integrating new PV capacity into the grid. This analysis indicates that cheaper total LCOE sites tend to be larger in capacity. The total capacity in this study was found to be far beyond the maximum peak load for the island. However, this study does not consider the economic and market potential for development. The cumulative capacity presented in this study assumes that the best locations are developed first and ignores the complex decision paths for new power plant development. Therefore, this analysis can only be treated as illustrative. Finally this study investigates the impact of inter-annual variability of resource using a variety of metrices including probability of exceedance and variation in capacity factor and LCOE. This study demonstrates that the capacity factor or LCOE could vary by over 10% year to year. This clearly indicates the risks involved in using any particular year of data and clearly points to the use of multi-year data to reduce some of the risks related to variability in weather.

14 SOLAR ENERGY↗

Influence of Lake Ice Biases in Reanalysis Data on Downscaled Climate Simulations over the Great Lakes Region

This data package contains observation-based and model-simulated datasets (all provided in NetCDF format) for evaluating how wintertime lake-ice representation affects regional weather and climate over the Laurentian Great Lakes (freshwater lake ecosystem) during the high–ice-cover winter of 2009. The observational component includes: (1) Stage IV gridded precipitation at 4 km, hourly resolution for January–February 2009 over the Great Lakes region (radar–gauge multisensor precipitation analyses); (2) Great Lakes Surface Environmental Analysis (GLSEA) satellite-derived lake-ice coverage at 1.3 km, daily resolution for the 2009 winter months, providing ice coverage over Lakes Superior, Michigan, Huron, Erie, and Ontario; and (3) in situ measurements at the Standard Rock site on Lake Superior from the Great Lakes Evaporation Network (GLEN) at hourly resolution, including near-surface atmospheric variables and sensible and latent heat fluxes (air–lake exchange) at a fixed point location. The modeling component provides corresponding fields from two simulations, both archived at 4 km, hourly resolution: a standalone Weather Research Forecasting model (WRF) run driven by the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis 5 (ERA5), and a two-way coupled model using WRF and the Finite Volume Community Ocean Model (WRF-FVCOM, a 3-D hydrodynamic lake model). These outputs include variables relevant to air–lake interaction and lake-effect processes (e.g., near-surface temperature, humidity, wind, precipitation, and surface turbulent fluxes), enabling direct comparison with the observational datasets. Users can analyze and visualize these NetCDF files with common tools such as Python (e.g., xarray, netCDF4, numpy, pandas), NCO/CDO, Panoply, or ncview; NetCDF variables can also be converted to other formats (e.g., CSV, GeoTIFF) using these utilities.

EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC TEMPERATU↗

Ultrafast Power Processor for Smart Grid: Power Module Development

This project’s goal was to increase the switching speed and decrease the losses of the power semiconductor devices and power switch modules necessary to enable Smart Grid energy flow and control equipment such as the Ultra-Fast Power Processor. The primary focus of this project involves exploiting the new silicon-based Super-GTO (SGTO) technology and build on prototype modules already being developed. The prototype super gate-turn-off thyristor (SGTO) has been tested fully under continuously conducting and double-pulse hard-switching conditions for conduction and switching characteristics evaluation. The conduction voltage drop measurement results indicate that SGTO has excellent conduction characteristics despite inconsistency among some prototype devices. Tests were conducted with two conditions: (1) fixed gate voltage and varying anode current condition, and (2) fixed anode current and varying gate voltage condition. The conduction voltage drop is relatively a constant under different gate voltage condition. In terms of voltage drop as a function of the load current, there is a fixed voltage drop about 0.5V under zero current condition, and then the voltage drop is linearly increased with the current. For a 5-kV voltage blocking device that may operate under 2.5-kV condition, the projected voltage drop is less than 2.5 V under 50-A condition, or 0.1%. If the device is adopted in a converter operating under soft-switching condition, then the converter can achieve an ultrahigh efficiency, typically above 99%. The two-pulse switching test results indicate that SGTO switching speed is very fast. The switching loss is relatively low as compared to that of the insulated-gate-bipolar-transistors (IGBTs). A special phenomenon needs to be noted is such a fast switching speed for the high-voltage switching tends to create an unexpected Cdv/dt current, which reduces the turn-on loss because the dv/dt is negative and increases the turn-off loss because the dv/dt is positive. As a result, the turn-on loss at low current is quite low, and the turn-off loss at low current is relatively high. The phenomenon was verified with junction capacitance measurement along with the dv/dt calculation. Under 2-kV test condition, the turn-on and turn-off losses at 25-A is about 3 and 9 mJ, respectively. As compared to a 4.5-kV, 60-A rated IGBT, which has turn-on and turn-off losses about 25 and 20 mJ under similar test condition, the SGTO shows significant switching loss reduction. The switching loss depends on the switching frequency, but under hard-switching condition, the SGTO is favored to the IGBT device. The only concern is during low current turn-on condition, there is a voltage bump that can translate to significant power loss and associated heat. The reason for such a current bump is not known from this study. It is necessary that the device manufacturer perform though test and provide the answer so the user can properly apply SGTO in pulse-width-modulated (PWM) converter and inverter applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Investigation of ion-beam machining methods for replicated x-ray optics

The final figuring step in the fabrication of an optical component involves imparting a specified contour onto the surface. This can be expensive and time consuming step. The recent development of ion beam figuring provides a method for performing the figuring process with advantages over standard mechanical methods. Ion figuring has proven effective in figuring large optical components. The process of ion beam figuring removes material by transferring kinetic energy from impinging neutral particles. The process utilizes a Kaufman type ion source, where a plasma is generated in a discharge chamber by controlled electric potentials. Charged grids extract and accelerate ions from the chamber. The accelerated ions form a directional beam. A neutralizer outside the accelerator grids supplies electrons to the positive ion beam. It is necessary to neutralize the beam to prevent charging workpieces and to avoid bending the beam with extraneous electro-magnetic fields. When the directed beam strikes the workpiece, material sputters in a predicable manner. The amount and distribution of material sputtered is a function of the energy of the beam, material of the component, distance from the workpiece, and angle of incidence of the beam. The figuring method described here assumes a constant beam removal, so that the process can be represented by a convolution operation. A fixed beam energy maintains a constant sputtering rate. This temporally and spatially stable beam is held perpendicular to the workpiece at a fixed distance. For non-constant removal, corrections would be required to model the process as a convolution operation. Specific figures (contours) are achieved by rastering the beam over the workpiece at varying velocities. A unique deconvolution is performed, using series-derivative solution developed for the system, to determine these velocities.

Drueding, Thomas W.↗

An Optimization Approach to Support Science Decision Making for Lunar Surface Exploration

Introduction: Scientific exploration is one of the three pillars of NASA’s Moon2Mars architecture, with crew surface extra vehicular activities (EVA) serving a critical enabling function. Development of surface EVA operational planning and execution, specifically integrating science and flight control teams (FCT), is currently being explored through analog scenarios. This integration, exercised, for example, through the Joint EVA and Hu-man Surface Mobility Test Team (JETT), allows for science input on EVA activities in near real-time through a Science Evaluation Room (SER), or Arte-mis science backroom, which integrates with the broader FCT through the Science Officer. The SER works within the FCT to support dynamic EVA planning in response to changes in operational constraints as well as science opportunities and re-prioritization, increasing the mission science return and accelerating the accomplishment of the Moon2Mars science objectives. The SER works within the FCT to provide recommendations to traverse execution in near real-time. One challenge is the requirement to deliver SER inputs to the FCT on operationally relevant timelines. Failure to do so may result in suboptimal execution of science exploration EVAs or even loss of key science objectives. To close this gap, we present a network optimization tool to allow the SER to provide rapid input to the FCT in response to changes in operational constraints or science opportunities. Inputs are predicated on approved science objectives, and clear rationale must be provided to the FCT for any requested change. Accordingly, this tool incorporates the Science Traceability Matrix (STM), SER prioritization scheme, and station characterization and action planning with operational constraints such as duration, traverse speed, and distance to maximize science objectives based on SER priorities, consistent with FCT operational requirements. Method: As a proof of concept, we used an existing linear programing software package used to simulate optimal routes through cellular metabolism. We built a Demonstrative Model with three STM objectives and four stations on a region of the Moon. The objectives were given an arbitrary prioritization and mapped to the stations through four possible crew actions. (Figs. 1 and 2). This station to STM mapping is consistent with the method used by the JETT5 Science Team to develop analog surface EVA science planning. We used a grid system with the landing site at the origin and the four stations placed across the positive x,y quadrant. Actions were assigned to each station and the accomplishment of those actions resulted in a numerical “reward” based on the ability of that action to achieve science objectives. The aggregate reward from each individual STM objective contributes to a global score (Science Yield), weighted by its priority. Operational constraints included a requirement to start and end at the landing site, 5 minutes each for initial station characterization and “clean up,” and variable total EVA time, traverse rate (fixed to 0.5 meters per second in our example), and time to perform each action (10, 5, 7, and 15 min for actions 1, 2, 3, and 4, respectively). Additional constraints and variables will be added in the future (e.g., sample mass, number of stations, traverse route constraints, illumination). Optimization. We converted the connections (arcs) between these stations (nodes) into a mixed integer linear programming optimization problem (arcs = constraints, nodes = variables) with the objective to maximize Science Yield. For any action, the Science Yield is equal to the relevance of that action to an STM objective [3, 2, and 1 point(s) for High, Med., and Low relevance, respectively], multiplied by the STM Objective Priority [3, 2, and 1 point(s) for High, Med., and Low priority, respectively]. This resulted in a model that computes the optimal station and action combination to maximize the Science Yield. These weightings can be adjusted by the SER as desired. Results: We explored three test cases for the Demonstrative Model. First, we set the maximum EVA duration to 120 minutes and computed the optimal route (Fig. 3A). The model suggested per-forming Actions 1 and 2 at Station P01, followed by Actions 1 and 2 at Station P02, and finally Actions 1 and 3 at Station P04 before returning to the Landing Site. Second, we adjusted the STM Objective Priori-ty order and computed the new optimal route (Fig. 3B). Under this situation, the model suggested per-forming all Actions at Station P02 followed by all Actions at Station P03. The previous test cases were relevant to SER planning activities. Next, we explored providing mid-EVA replanning input to the FCT. Scenario: While executing the Route in Fig. 3A the crew finishes at Station P01 and FCT decides that the EVA needs to finish in 45 minutes back at the Landing Site. FCT asks SER to recommend changes to the plan to accommodate this operation-al change. Using the model and incorporating these new constraints (start at Station P01, max. time of 45 min), the model suggested performing Actions 2 and 4 at Station P03 (Fig. 4), requiring 41 minutes to complete and return to the Landing Site. Interestingly, Station 3 was not part of the original route. Using the model, we determined the EVA would need 66 minutes, instead of 45, in order for the original Station P04 to yield a larger Science Yield than Station P03. The parametrization and simulation was per-formed in less than a minute, demonstrating the operational relevance of the approach. Future Efforts: The results from the Demonstrative Model suggest this tool can accelerate SER decision making on operationally relevant timelines. Use in analog activities, such as JETT5 or follow-ons, which have over a dozen stations for a crew to explore and over a dozen actions per station, will provide needed validation of the utility of this tool for planning EVAs, replanning mid-EVA, or planning follow-on EVAs based on previous results. Further integration with FCT execution monitoring tools may provide additional efficiency gains, al-lowing rapid and iterative exploration of operation-al and science decision space by the FCT and SER.

Science Operations↗

Deep Reinforcement Learning-Based Control of Energy Storage for Interarea Oscillation Damping

With the increasing electricity consumption and lack of transmission investment, today's power systems are operated much closer to their limits, raising concerns of inter-area oscillations that deteriorate the system stability. Here, this article presents a novel energy storage placement and control approach for enhanced damping of interarea oscillations. Combining the residual analysis and dominant mode analysis, we are able to identify the advantageous locations for placing energy storage that achieve improved damping performance. To overcome the challenges, such as fixed control parameters and insufficient damping, we propose to use a deep reinforcement learning-based approach for energy storage control. A state-of-the-art guided surrogate-gradient-based evolutionary strategy is used to train a learning agent in a robust, efficient, and reproducible manner. Parallel computing is also adopted to speed up the training process. The proposed strategy has been tested on both medium and large-scale systems. The proposed methods have demonstrated their effectiveness in mitigating various interarea oscillations within a timeframe of 20 s, thereby averting system collapse and enhancing power grid stability effectively.

25 ENERGY STORAGE↗

Machine learning changes the rules for flux limiters

Learning to integrate non-linear equations from highly resolved direct numerical simulations has seen recent interest for reducing the computational load for fluid simulations. Here, we focus on determining a flux-limiter for shock capturing methods. Focusing on flux limiters provides a specific plug-and-play component for existing numerical methods. Since their introduction, an array of flux limiters has been designed. Using the coarse-grained Burgers' equation, we show that flux-limiters may be rank-ordered in terms of their log-error relative to high-resolution data. We then develop a theory to find an optimal flux-limiter and present flux-limiters that outperform others tested for integrating Burgers' equation on lattices with [Formula: see text], and 2x, 3x, 4x, and 8x coarse-grainings. We train a continuous piecewise linear limiter by minimizing the mean-squared misfit to six-grid point segments of high-resolution data, averaged over all segments. While flux limiters are generally designed to have an output of φ(r) = 1 at a flux ratio of r = 1, our limiters are not bound by this rule and yet produce a smaller error than standard limiters. Here we find that our machine learned limiters have distinctive features that may provide new rules-of-thumb for the development of improved limiters. Additionally, we use our theory to learn flux-limiters that outperform standard limiters across a range of values (as opposed to at a specific fixed value) of coarse-graining, number of discretized bins, and diffusion parameter. This demonstrates the ability to produce flux limiters that should be more broadly useful than standard limiters for general applications.

97 MATHEMATICS AND COMPUTING↗

Hierarchical Fractional Advection-Dispersion Equation (FADE) to Quantify Anomalous Transport in River Corridor over a Broad Spectrum of Scales: Theory and Applications

Fractional calculus-based differential equations were found by previous studies to be promising tools in simulating local-scale anomalous diffusion for pollutants transport in natural geological media (geomedia), but efficient models are still needed for simulating anomalous transport over a broad spectrum of scales. This study proposed a hierarchical framework of fractional advection-dispersion equations (FADEs) for modeling pollutants moving in the river corridor at a full spectrum of scales. Applications showed that the fixed-index FADE could model bed sediment and manganese transport in streams at the geomorphologic unit scale, whereas the variable-index FADE well fitted bedload snapshots at the reach scale with spatially varying indices. Further analyses revealed that the selection of the FADEs depended on the scale, type of the geomedium (i.e., riverbed, aquifer, or soil), and the type of available observation dataset (i.e., the tracer snapshot or breakthrough curve (BTC)). When the pollutant BTC was used, a single-index FADE with scale-dependent parameters could fit the data by upscaling anomalous transport without mapping the sub-grid, intermediate multi-index anomalous diffusion. Pollutant transport in geomedia, therefore, may exhibit complex anomalous scaling in space (and/or time), and the identification of the FADE’s index for the reach-scale anomalous transport, which links the geomorphologic unit and watershed scales, is the core for reliable applications of fractional calculus in hydrology.

97 MATHEMATICS AND COMPUTING↗

Conservation equations and physical models for hypersonic air flows over the aeroassist flight experiment vehicle

The code development and application program for the Langley Aerothermodynamic Upwind Relaxation Algorithm (LAURA), with emphasis directed toward support of the Aeroassist Flight Experiment (AFE) in the near term and Aeroassisted Space Transfer Vehicle (ASTV) design in the long term is reviewed. LAURA is an upwind-biased, point-implicit relaxation algorithm for obtaining the numerical solution to the governing equations for 3-D, viscous, hypersonic flows in chemical and thermal nonequilibrium. The algorithm is derived using a finite volume formulation in which the inviscid components of flux across cell walls are described with Roe's averaging and Harten's entropy fix with second-order corrections based on Yee's Symmetric Total Variation Diminishing scheme. Because of the point-implicit relaxation strategy, the algorithm remains stable at large Courant numbers without the necessity of solving large, block tri-diagonal systems. A single relaxation step depends only on information from nearest neighbors. Predictions for pressure distributions, surface heating, and aerodynamic coefficients compare well with experimental data for Mach 10 flow over an AFE wind tunnel model. Predictions for the hypersonic flow of air in chemical and thermal nonequilibrium over the full scale AFE configuration obtained on a multi-domain grid are discussed.

Gnoffo, Peter A.↗

Shock-Buffet Prediction Report in Support of the High Angle Working Group at the Third Aeroelastic Prediction Workshop

This paper presents a summary of the computational shock-buffet results associated with the third Aeroelastic Prediction Workshop (AePW-3) High-Angle Working Group. The computational results are compared against experimental data collected during the Oscillating Turn Table (OTT) Benchmark Supercritical Wing (BSCW) test campaign conducted in NASA Langley Research Center Transonic Dynamics Tunnel (TDT) in early 2000. In addition to experimental forced oscillation data, unsteady pressure data was collected at a single spanwise station at transonic Mach numbers, several values of dynamic pressure, and fixed angles of attack. It is acknowledged that the current experimental data are limited, but future experiments are planned to obtain pressure data at two wingspan stations in addition to unsteady Pressure Sensitive Paint (uPSP). With that, the computational results presented here are considered to be semi-blind. The results are presented in the form of time-varying pressure coefficients, running-mean values of the pressure coefficients, Power Spectral Density (PSD) and Strouhal number computations. The results are split into two parts. In the first part, the computational results obtained by each team using their flow solvers and grids are compared. In the second part, a single computational tool was used to compute unsteady pressure on participant-generated grids. In addition, a description of each participating team’s software and methods is included.

Pawel Chwalowski↗

Optimal Variable Switching Frequency Scheme to Reduce Loss of Single-Phase Grid-Connected Inverter With Unipolar and Bipolar PWM

Reducing the power loss of a converter without increasing its volume or cost in hardware has always been a much sought-after but challenging goal. This article proposes a comprehensive variable switching frequency (VSF) scheme to improve the overall system efficiency while still meeting a given total harmonic distortion (THD) requirement without any hardware changes, achieved only by changes to the controller. In this article, it is analyzed that for the H-bridge inverter, the inductor copper loss and the switch conduction loss are independent of the switching frequency (SF), while the device switching loss and the inductor core loss are functions of the SF. This article aims at weighting the combined switching loss and inductor core loss for both the unipolar and bipolar modulation techniques, with the constraint on the output THD, which, for fixed passive components, is a function of inductor ripple current that in turn depends on the SF. An optimal VSF scheme is devised through rigorous mathematical analysis of the output ripple component and the SF-dependent losses. In each switching cycle, the inductor ripple current is predicted with the circuit parameters, such as duty cycle, switching period, inductance, and dc voltage, and by implementing the VSF scheme, the current ripple is optimally varied such as to satisfy the THD requirement while reducing the SF-dependent losses. A generalized method to design VSF schemes for any topology and specifications is also presented, which would help future users in designing the VSF controller. A 1-kW H-bridge inverter using SiC MOSFETs and powdered iron/ferrite core has been built to validate the theoretical analysis. Both constant SF (CSF) scheme (200 kHz) and optimal VSF scheme with simple controller modification have been implemented in the experimental prototype using DSP TMS320f28335. Compared with the CSF scheme, the optimal VSF scheme shows a significant improvement in the system efficiency at rated power from 94.7%...

conduction loss↗

A critical analysis of the ultraviolet temperature scale of the helium-dominated DB and DBV white dwarfs

The temperatures of the hottest of the DB and of some of the variable DBV white dwarfs have been reanalyzed, using a new helium-rich model atmosphere grid and archival IUE data. The grid covers variations in the effective temperature, surface gravity, and trace hydrogen abundance. Significantly lower temperatures than those found by earlier investigations are found. This has influence on the issue of which mixing-length theory is the best one for treatment of convection in DB white dwarfs. The prototype of the DBV stars, GD 358, is given particular attention in view of the recently reported HE II 1640-A line. The sensitivity of the new results to input physics is analyzed. It is found that uncertainties in Stark broadening parameters, convective efficiency, and equation of state and the assumptions of a fixed gravity (log g = 8) and a negligible abundance of hydrogen can at most give an error in the effective temperature of 400 K for a typical DB star. The uncertainty on the absolute calibration of the IUE cameras and the effect of small interstellar reddening dominate the error analysis.

Thejll, Peter↗

SU-F-T-590: Modeling PTV Dose Fall-Off for Cervical Cancer SBRT Treatment Planning Using VMAT and Step-And-Shoot IMRT

Purpose: Due to the high dose per fraction in SBRT, dose conformity and dose fall-off are critical. In patients with cervical cancer, rapid dose fall-off is particularly important to limit dose to the nearby rectum, small bowel, and bladder. This study compares the target volume dose fall-off for two radiation delivery techniques, fixed-field IMRT & VMAT, using non-coplanar beam geometries. Further comparisons are made between 6 and 10MV photon beam energies. Methods: Eleven (n=11) patients were planned in Pinnacle3 v9.10 with a NovalisTx (HD120 MLC) machine model using 6 and 10 MV photons. The following three techniques were used: (1) IMRT (10 non-coplanar beams) (2) Dual, coplanar 360° VMAT arcs (4° spacing), and (3) Triple, non-coplanar VMAT arcs (1 full arc and dual partial arcs). All plans were normalized such that 98% of the PTV received at least 28Gy/4Fx. Dose was calculated using a 2.0mm isotropic dose grid. To assess dose fall-off, twenty concentric 2mm thick rings were created around the PTV. The maximum dose in each ring was recorded and the data was fitted to model dose fall-off. A separate analysis was performed by separating target volumes into small (0–50cc), medium (51–80cc), and large (81–110cc). Results: Triple, non-coplanar VMAT arcs showed the best dose fall-off for all patients evaluated. All fitted regressions had an R{sup 2}≥0.99. At 10mm from the PTV edge, 10 MV VMAT3-arc had an absolute improvement in dose fall-off of 3.8% and 6.9% over IMRT and VMAT2-arc, respectively. At 30mm, 10 MV VMAT3-arc had an absolute improvement of 12.0% and 7.0% over IMRT and VMAT2-arc, respectively. Faster dose fall-off was observed for small volumes as opposed to medium and large ones—9.6% at 20mm. Conclusion: Triple, non-coplanar VMAT arcs offer the sharpest dose fall-off for cervical SBRT plans. This improvement is most pronounced when treating smaller target volumes.

60 APPLIED LIFE SCIENCES↗

Computational fluid dynamics study of the variable-pitch split-blade fan concept

A computational fluid dynamics study was conducted to evaluate the feasibility of the variable-pitch split-blade supersonic fan concept. This fan configuration was conceived as a means to enable a supersonic fan to switch from the supersonic through-flow type of operation at high speeds to a conventional fan with subsonic inflow and outflow at low speeds. During this off-design, low-speed mode of operation, the fan would operate with a substantial static pressure rise across the blade row like a conventional transonic fan; the front (variable-pitch) blade would be aligned with the incoming flow, and the aft blade would remain fixed in the position set by the supersonic design conditions. Because of these geometrical features, this low speed configuration would inherently have a large amount of turning and, thereby, would have the potential for a large total pressure increase in a single stage. Such a high-turning blade configuration is prone to flow separation; it was hoped that the channeling of the flow between the blades would act like a slotted wing and help alleviate this problem. A total of 20 blade configurations representing various supersonic and transonic configurations were evaluated using a Navier Stokes CFD program called ADAPTNS because of its adaptive grid features. The flow fields generated by this computational procedure were processed by another data reduction program which calculated average flow properties and simulated fan performance. These results were employed to make quantitative comparisons and evaluations of blade performance. The supersonic split-blade configurations generated performance comparable to a single-blade supersonic, through-flow fan configuration. Simulated rotor total pressure ratios of the order of 2.5 or better were achieved for Mach 2.0 inflow conditions. The corresponding fan efficiencies were approximately 75 percent or better. The transonic split-blade configurations having large amounts of turning were able to generate large amounts of total turning and achieve simulated total pressure ratios of 3.0 or better with subsonic inflow conditions. These configurations had large losses and low fan efficiencies in the 70's percent. They had large separated regions and low velocity wakes. Additional turning and diffusion of this flow in a subsequent stator row would probably be very inefficient. The high total pressure ratios indicated by the rotor performance would be substantially reduced by the stators, and the stage efficiency would be substantially lower. Such performance leaves this dual-mode fan concept less attractive than originally postulated.

Kepler, C. E.↗

Study of CFD Variation on Transport Configurations from the Second Drag-Prediction Workshop

This paper describes and analyzes a series of nearly 90 CFD test cases performed as a contribution to the second Drag Prediction Workshop, held in association with the AIAA in June 2003. Two configurations are included: DLR-F6 wing-body and wing-body-nacelle-pylon. The ability of CFD to predict the drag, lift, and pitching moment from experiment-including the "delta" arising from the addition of the nacelle and pylon-is assessed. In general, at a fixed angle of attack CFD overpredicts lift, but predicts the delta C (sub L) reasonably well. At low lift levels (C (sub L) less than 0.3)), delta C (sub D) is 20-30 drag counts (30-45%) high. At the target lift coefficient of C(sub L) = 0.5, delta C (sub D) is overpredicted by between 11-16 counts. However, the primary contribution of this paper is mot so much the assessment of CFD against experiment, but rather a detailed assessment and analysis of CFD variation. The series of test cases are designed to determine the sensitivity/variability of CFD to a variety of factors, including grid, turbulence model, transition code, and viscous model. Using medium-level grids (6-11 million points) at the target lift coefficient, the maximum variation in drag due to different grids is 5-11 drag counts, due to code is 5-10 counts, due to turbulence model is 7-15 counts, due to transition is 10-11 counts, and due to viscous model is 4-5 counts. Other specific variations are described in the paper.

Christopher L Rumsey↗

Real-time Implementation of a Dual-Active-Bridge Based Multi-Level Photovoltaic Converter

Silicon-carbide based, multi-level converters with dual-active-bridge (DAB) are getting attention for medium voltage, direct grid-connected, utility-scale photovoltaic (PV) applications due to their higher efficiency and power density. To de-risk complex control development for these high-voltage and high-power inverters, hardware-in-the-loop techniques are often required. Due to the high switching frequency and the large number of power electronic switches, off-the-shelf, real-time simulation tools are not yet fully developed for this application, even with FPGA-based simulators. To address this, a new co-simulation approach in FPGA is presented that utilizes Time-Stamped Bridge (TSB) for the higher frequency converters along with detailed fixed conductance based discrete device simulation of the rest of the circuit. A complex DAB-based PV converter with maximum switching frequency of 50 kHz is successfully simulated in real-time in the FPGA and the results are compared with offline simulation results. A controller hardware-in-the-loop (CHIL) platform is developed to demonstrate real-time, closed-loop test results for this DAB-based PV converter.

Dong, Zerui↗

High-order methods for wind turbine simulations and moving to next-generation platforms

The goal of the ExaWind project is to enable predictive simulations of wind farms comprised of many megawatt-scale turbines situated in complex terrain. Predictive simulations will require computational fluid dynamics (CFD) simulations for which the mesh resolves the geometry of the turbines and captures the rotation and large deflections of blades. Whereas such simulations for a single turbine are arguably petascale class, multi-turbine wind farm simulations will require exascale-class resources. The primary physics codes in the ExaWind project are Nalu-Wind, which is an unstructured-grid solver for the acoustically incompressible Navier-Stokes equations, and OpenFAST, which is a whole-turbine simulation code. The Nalu-Wind model consists of the mass-continuity Poisson-type equation for pressure and a momentum equation for the velocity. For such modeling approaches, simulation times are dominated by linear-system setup and solution for the continuity and momentum systems. For the ExaWind challenge problem, the moving meshes greatly affect overall solver costs as reinitialization of matrices and recomputation of preconditioners is required at every time step. This milestone represents an effort to increase the fidelity of Nalu-Wind at a fixed resolution through the implementation of a tensor-product based, matrix-free high order scheme. High order finite element methods have increased local work per datum communicated and have the potential to provide significantly more accurate solutions at a fixed number of degrees of freedom. Previous to this milestone, Nalu-Wind had an arbitrary order Control Volume Finite Element Method discretization as a solver option, but it required too much memory and was too slow to be of practical use. The work in this milestone addresses these issues by first implementing an implicit, high order solver that only partially assembles the global system. This reduces the memory footprint of the high-order scheme by orders of magnitude for higher polynomial orders. Second, a faster, tensor-product based method for evaluating the action of the left-hand side was implemented. This reduces the amount of computational work required by the scheme and dramatically enhanced the time-to-solution on example problems. Finally, this milestone is an evaluation of the value of high order methods in the wind application space. With the enhancements to memory and computational cost, accuracy vs. time-to-solution was evaluated for several resolutions on an under-resolved Taylor Green vortex test case. Results show that the high order scheme is cost-competitive with the production low-order schemes in Nalu-Wind, being moderately more expensive than the production edge-based vertex centered finite volume scheme. The evaluation of accuracy on the test case shows a potential benefit to high order at the highest resolution while not deteriorating accuracy on the lowest tested resolution. More work is needed to show value in the wind application, but positive strides have been made.

17 WIND ENERGY↗

Resolving the Discontinuity Between Thermal Scattering Data and Fast Data

The task of resolving discontinuities between thermal cross sections and fast cross sections in AMPX processing is part of a broader project to provide guidance on the potential effect of unknown thermal neutron scattering law (TNSL) data, primarily from the standpoint of criticality safety. The primary goal of this work is to deliver code fixes in AMPX that increase confidence that SCALE libraries provide physically correct cross sections across the full range of neutron energies encountered in transport applications. This report discusses the resolution of two sources of discontinuity. The first issue occurs when the Bragg edges in an evaluated nuclear data file do not extend to 5 eV. The second issue concerns parameters chosen during the processing of the nuclear data library—specifically, the parameter that defines the energy at which the thermal data ends and the fast nuclide data begins. This report also discusses a third issue, which is related to the calculation of probability distributions from a densely gridded double-differential cross section.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗