Computer-simulated ion-emission images of dislocations - Screw dislocation at the center of /420/.
Dislocation in field-ion micrograph analyzed by computer-simulated Ranganathan hypothesis using Moore shell model
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Dislocation in field-ion micrograph analyzed by computer-simulated Ranganathan hypothesis using Moore shell model
Using Cornell's supercomputing facilities, an extensive study of the Moore-Greitzer model was carried out, which gives accurate and reliable information about compressor instability. The bifurcation analysis in the companion paper shows the dependence of the mode of compressor response on the shape of the rotating stall characteristic. The numerical results verify and extend this with a more accurate representation of the characteristic. The effect of the parameters on the shape of the rotating stall characteristic is investigated, and it is found that the parameters with the strongest effects are the inlet length, and the shape of the compressor pressure rise vs. mass flow diagram (i.e. tall diagrams vs. shallow diagrams). The effects of inlet guide vane loss on the characteristic are discussed.
With a one-mode truncation it is possible to reduce the Moore-Greitzer model for compressor instability to a set of three ordinary differential equations. These are approached from the point of view of bifurcation theory. Most of the bifurcations emerge from a degenerate Takens-Bogdanov bifurcation point. The bifurcation sets are completed using the numerical branch tracking scheme AUTO. Despite the severity of the truncation, the agreement with experimental results is excellent.
Ocean observation buoys require relatively small amounts of power, yet traditionally necessitate costly resupply trips for battery replacement. With the offshore location of the buoys and small power requirements, wave energy may be an effective solution for providing consistent and reliable power to support the buoy instrumentation. The US National Science Foundation Ocean Observatories Initiative (OOI) includes arrays of point absorber-like buoy systems used for ocean observation that have been deployed at multiple locations including the Southern Mid-Atlantic Bight. A study is currently underway to design a pitch resonator wave energy converter to supplement existing renewable energy generation for powering observation instrumentation. This paper details field measurements from surface moorings of the OOI Coastal Pioneer Array, which informs the subsequent development of a numerical model for the moored observation system. The model is developed in Wave Energy Converter Simulator (WEC-Sim), which leverages the Simscape multibody solver within the MATLAB/Simulink framework and linear potential flow theory to simulate the hydrodynamic interactions and multibody dynamics in 6 degrees of freedom. Multiple tuning variables are considered to produce a model for the system that matches well with empirical data (about 8% error). In conclusion, the WEC-Sim model will serve as a platform for integrating the pitch resonator wave energy converter concept and deployment preparation (detailed design including power take-off and control systems, response evaluation, etc.).
As wave energy converters (WECs) become more advanced and cost-efficient, so too must their mooring systems. A key question in the development plans for WECs is the cost of the mooring system, particularly for large wave farms. WEC devices deployed in a WEC farm array, where each device can be connected by shared mooring lines in various array layouts, have potential to reduce mooring system costs significantly. This paper presents the modeling and designing of mooring systems for large WEC arrays and the calculation of the cost of each mooring system to determine the change in cost as the number of WECs in a farm increases. A baseline mooring system for a single floating oscillating water column (OWC) WEC was developed for this analysis. The mooring system utilizes four anchored mooring lines connected to a square assembly of wire rope mooring lines, supported by four floating buoys, and attached to the floating WEC by four polyester rope mooring lines. This assembly, referred to as a floating cell, can be tiled to form various rectangular WEC arrays. The objective of this analysis is to determine how the mooring system cost changes as more WECs are added to an array layout, each with their own interconnected floating cell. To do this, complete mooring systems need to be designed for each WEC array layout. To narrow down the design space of a WEC array mooring system, a couple assumptions were made. It was assumed that the floating cell parameters of the baseline design were to stay constant across all floating cells in the WEC array. It was also assumed that the anchored mooring lines would be of the baseline configuration, a predominantly chain mooring line with a short section of polyester rope near the fairlead, and a drag-embedment anchor. These anchored lines were assumed to extend from the outer edges of the WEC array, inline with the headings of the wire rope mooring lines of the floating cells, or diagonal if extending from a corner of the WEC array. Full mooring systems were designed for 2xN and NxN WEC array layouts and efficiently simulated in the mooring dynamics simulation tool, MoorDyn, to ensure all dynamic constraints were met. The system costs were calculated and then refined by shortening unnecessary chain line lengths and reducing the chain diameters of the downstream anchored mooring lines. It was found that, in general, mooring system costs per WEC decrease when WECs are installed in an array. Compared to the baseline mooring system for a single WEC, the 2x3 mooring system array had the lowest mooring system cost per WEC, reducing the cost per WEC by 59%. The 3x3 and 4x4 array mooring systems also saw significant reductions in cost per WEC but had negligible cost savings between the two designs, primarily because the larger 4x4 mooring system requires larger chain diameters, which increases cost. These results provide an interesting glimpse into modeling, designing, and calculating the cost of mooring systems for large WEC arrays.
When a compression system goes unstable, the mode of response depends on the operating and system parameters, such as throttle setting and B parameter. Previous numerical work on the model developed by Moore and Greitzer (1986) has provided a limited picture of the parametric effects. Applying bifurcation theory to a single-harmonic version of the model has supplied much more complete information, defining the boundaries of each mode of response in the parameter space. Specifically, this is shown in a plot of B vs. throttle setting, which compares well with the corresponding map produced experimentally. The importance of the shape of the rotating stall characteristic is emphasized. The analysis shows a qualitative difference between classic surge and deep surge.
This study evaluates the feasibility, accuracy, and limitations of using 1/100th scale physical mooring systems to represent full-scale mooring behavior for wave energy converters (WECs) during small-scale tank testing. The work focuses on an RM3-style point absorber deployed in conditions representative of the PacWave South test site and examines whether small-scale physical testing can reliably inform numerical modeling, design decisions, and future prototype development. Overall, this study concludes that small-scale (1/100th) physical mooring models can provide valuable qualitative insights, including relative comparisons between mooring types and trends in device behavior, but cannot reliably replicate full-scale mooring loads or dynamic response without significant scaling distortion. Physical tests at this scale are most appropriate for motion characterization and model validation within known limitations, not for deriving absolute mooring loads or final engineering design values. Key lessons learned emphasize the importance of improved instrumentation strategies, iterative wave tank tuning, more precisely manufactured scaled mooring components, and enhanced anchoring systems to reduce experimental uncertainty.
A structured study effort to develop an extensive, innovative set of mobility and navigation concepts for a planetary exploration vehicle along with the concomitant value system and evaluation tools is presented. A further objective is to submit these concepts to a rigorous, structured evaluation process to derive the most promising candidate systems. To support the evaluation process, a three-layer computer model of the Martian surface was developed, based on the 1/64 deg Digital Elevation Model (DEM) of Mars. Local surface roughness based on measured Martian slope distribution and power spectral density was superimposed on the DEM, and rocks based on Moore's distribution model were added. To assess performance, selected concepts were modeled using DADS, and simulations were run with the vehicle traversing the Martian surface model, including one-meter-high vertical steps and one-meter-wide crevasses. The design details of three promising candidate systems are presented, along with the discussion of their evolution with some recommendations.
There is a lack of suitable numerical tools, particularly open-source tools, that can be used for designing and optimizing marine turbine systems. The National Renewable Energy Laboratory (NREL) has added features to their widely used mid-fidelity wind turbine modeling code, OpenFAST, to enable modeling of axial flow marine turbines. This necessitated the addition of several physical effects relevant to marine turbines that can be neglected for wind turbines. These include buoyant loads, added mass and inertia loads, wave-current superposition, and changes to the coordinate systems. This updated version of OpenFAST allows for the modeling of both fixed and floating marine turbine systems at a speed comparable to real time. While efficient for long simulations, large sets of load cases, and design studies, mid-fidelity codes cannot capture all of the potentially important physical phenomenon impacting marine turbine systems. High-fidelity computational fluid dynamics (CFD) simulations can capture more flow effects with fewer assumptions and provide detailed body pressure mapping and flow-field information. It is important to compare predictions between mid-fidelity and high-fidelity codes, both to verify the models and to understand the limitations. A floating marine turbine system designed by NREL was modeled both with OpenFAST and with the commercial CFD code, STARCCM+. The CFD model used a 3-D unsteady Reynolds-averaged Navier-Stokes solver for a volume-of-fluid numerical wave and current tank. The blade-resolved simulations used the sliding-interface technique for the spinning rotor and an overset grid to accommodate the rigid-body motion of the floating system. The mooring system was modelled with a custom coupling of the CFD solver with the open-source code, MoorDyn. This improves upon the existing quasi-static catenary solver in STARCCM+, which lacks seabed contact or line-to-line connections. Spatial and temporal convergence studies were conducted. The simulation results for a combined current and wave condition are compared between OpenFAST and CFD, highlighting the capabilities of the mid-fidelity code and identifying the areas where a high-fidelity approach is needed.
As a continuation of the work of Moore et al. (1991), who found evidence that coronal holes are heated by Alfven waves that are reflected back down within the coronal holes, this paper shows that to demonstrate this evidence, it is only necessary to consider a subset of the Moore et al. models, namely, those having radial magnetic field. Using these models, it is shown that the Alfven velocity is not constant in the atmosphere of coronal holes, but changes with height (or radius), causing downward reflection of all upward Alfven waves of sufficiently long wavelength (or period).
There is a lack of suitable numerical tools, particularly open-source tools, that can be used for designing and optimizing marine turbine systems. The National Renewable Energy Laboratory has added features to their widely used mid-fidelity wind turbine modeling code, OpenFAST, to enable modeling of axial-flow marine turbines. This necessitated the addition of several physical effects relevant to marine turbines that are neglected for wind turbines. These include buoyancy, added mass and inertial loads, wave-current superposition, and changes to the coordinate systems. This updated version of OpenFAST allows for the modeling of both fixed and floating marine turbines at a speed comparable to real time. While efficient for large sets of load cases and design studies, mid-fidelity codes make simplifying assumptions that may impact their accuracy. High-fidelity computational fluid dynamics (CFD) simulations can capture more flow effects with fewer assumptions and provide detailed body pressure mapping and flow-field information. It is important to compare predictions between mid-fidelity and high-fidelity codes, both to verify the models and to understand the limitations. A floating marine turbine system was modeled both with OpenFAST and with the commercial CFD code STAR-CCM+. The CFD model used a three-dimensional unsteady Reynolds-averaged Navier-Stokes solver for a volume-of-fluid numerical wave and current tank. The blade-resolved simulations used the sliding-interface technique for the spinning rotor and an overset grid to accommodate the rigid-body motion of the floating system. The mooring system was modeled with a custom coupling of the CFD solver with the open-source code MoorDyn. This improves upon the existing quasi-static catenary solver in STAR-CCM+, which lacks seabed contact or line-to-line connections. Simulation results for a floating marine turbine are compared between OpenFAST and CFD, highlighting the capabilities of the mid-fidelity code and identifying the areas where a high-fidelity approach is needed.
Low altitude flight in urban areas is susceptible to degraded GNSS-based navigation system performance due to terrain interference with radio signals from orbital positioning satellites. Predictive navigation performance fidelity tools are needed a) in preflight planning to assist in the creation of safe flight paths and b) in-flight to provide contingency management agents with the navigation risk of proximal flight corridors. Two navigation fidelity prediction services are validated by comparison with over 6000 readings from GNSS sensors collected along a five-mile path through urban areas of Corpus Christi, Texas, on three dates in 2022. Predictions are based on satellite line of sight through 3D terrain data collected in 2018. Each service predicts a set of navigation fidelity metrics over a user-specified time period. One metric estimated by both is the number of visible satellites. A direct comparison of the number of predicted visible satellites with the number sensed by the receiver is used to validate the prediction services. Results show an exact match in the number of predicted satellites for 60% of the measurements, and a match within +/- 4 satellites for 95% of the measurements. As expected, agreement improves away from vertical blocking terrain. Most cases of mismatch are due a lower predicted count than measured (false negatives), and can be accounted for by receiver pickup of stray signals caused by multipath propagation. About 10% of mismatches are false positives and are mostly accounted for by foliage effects. The two services predict visibility of the same set of satellites 80% of the time, differ by two or less satellites 95% of the time, and can compute predictions for one hour of observations in one minute or less. Validation is analyzed statistically and in detailed case studies of selected observation times. The prediction services validated in this study run fast enough for preflight safety planning. The more stringent challenge of inflight navigation fidelity prediction for contingency management requires both a speedup of the current level of modeling and equally fast stray signal modeling.
With the end of Moore’s law and Dennard scaling, efficient training increasingly requires rethinking data volume. Can we train better models with significantly less data via intelligent subsampling? To explore this, we develop SICKLE, a sparse intelligent curation framework for efficient learning, featuring a novel maximum entropy (MaxEnt) sampling approach, scalable training, and energy benchmarking. We compare MaxEnt with random and phase-space sampling on large direct numerical simulation (DNS) datasets of turbulence. Evaluating SICKLE at scale on Frontier, we show that subsampling as a preprocessing step can, in many cases, improve model accuracy and substantially lower energy consumption, with observed reductions of up to 38×.
We present model line profiles of [O II] lambda3727, [Ne III] lambda3869, [O I] lambda5007, [Fe VII] lambda6087, [Fe X] lambda6374, [O I] lambda6300, H(alpha) lambda6563, and [S 2] lambda6731. The profiles presented here illustrate explicitly the pronounced effects that collisional de-excitation, and that spatial variations in both the ionization parameter and cloud column density, have on Narrow-Line Region (NLR) model profiles. The above effects were included only qualitatively in a previous analytical treatment by Moore and Cohen. By making a direct correspondence between these model profiles and the analytical model profiles of Moore and Cohen, and by comparing with the observed profiles presented in a companion paper and also with those presented elsewhere in the literature, we strengthen some of the conclusions of Moore and Cohen. Most notably, we argue for constant ionization parameter, uniformly accelerated outflow of clouds that are individually stratified in ionization, and the interpretation of emission-line width correlations with ionization potential as a column density effect. For comparison with previous observational studies, such as our own in a companion paper, we also calculate profile parameters for some of the models, and we present and discuss the resulting line width correlations with critical density (n(sub cr)) and Ionization Potential (IP). Because the models we favor are those that produce extended profile wings as observed in high spectral resolution studies, the line width correlations of our favoured models are of particular interest. Line width correlations with n(sub cr) and/or IP result only if the width parameter is more sensitive to extended profile wings than is the Full Width at Half-Maximum (FWHM). Correlations between FWHM and n(sub cr) and/or IP result only after convolving the model profiles with a broad instrumental profile that simulates the lower spectral resolution used in early observational studies. The model in agreement with the greatest number of observational considerations has electron density decreasing outward from n(sub e) approx. equals 10(exp 6)/cu cm to n(sub e) approx. equals 10(exp 2)/cu cm and, due to collisional de-excitation effects in the lowest velocity clouds, it generates broad flat-topped profile peaks in the lines of lowest critical density (e.g., [O II] lambda3727 and [S II] lambda(lambda)6716, 6731). Because the observed profile peaks of both low and high critical density lines are often very similar, our favored model requires a contribution to NLR emission-line spectra from low-velocity, low-density, and low-ionization gas not included in the model NLR.
Shared mooring lines are a method to reduce the stationkeeping cost of floating offshore wind farms; however, their impacts on floating array dynamics are not yet well understood. Here this article presents advancements to floating wind farm simulation capabilities that allow the dynamic modeling of shared-mooring floating wind arrays - specifically, platform coupling through shared lines and proper phasing of wave loads across the array. These capabilities are demonstrated on a 10-turbine shared-mooring array featuring two staggered rows of wind turbines. A baseline array design with individually moored turbines is used as a basis for comparison. Coupled analysis using FAST.Farm shows that the shared-mooring design has smaller fluctuations in surge when compared to the baseline design. The mean and maximum platform offsets are highest in normal operating conditions, but the maximum mooring line tensions are highest in 50-year storm conditions. Power spectral density analysis of platform surge and sway motions shows that the shared mooring configuration does not introduce any significant inter-platform resonances. The tower-base bending moment statistics and the line tension damage equivalent loads indicate no consequential differences in turbine loading or mooring fatigue life. Anchor load analysis shows that the total required anchor capacity for the shared-mooring array is decreased by approximately 25% when shared anchors are used. Dynamic simulations of the shared mooring system under line failures show that remaining line tensions stay within bounds and that offsets are significantly smaller when compared to the baseline design. Overall, the results show that shared moorings do not introduce any dynamic response concerns in this floating wind array design.
The DeepFarm project, led by Principle Power Inc (PPI), focused on design, modeling and development of innovative mooring and anchoring systems for semi-submersible floating wind turbine platforms in a deep water, commercial-size wind farm. It explored the possibility of sharing anchors amongst the floating platforms within the farm, and considers site conditions representative of the West Coast and Hawaii, with a variety of water depths, as case studies to ensure that the sensitivity to water depth and park size are well understood. NREL and PPI worked together to develop and apply NREL's computational tools for modeling floating wind farm dynamics and costs.
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