Frequency Scans for GFM Performance Verification
This presentation shows how frequency scan tests of inverter-based resources can be used to define specifications for grid-forming (GFM) control.
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This presentation shows how frequency scan tests of inverter-based resources can be used to define specifications for grid-forming (GFM) control.
A framework for parallel unstructured grid generation targeting both shared memory multi-processors and distributed memory architectures is presented. The two fundamental building-blocks of the framework consist of: (1) the Advancing-Partition (AP) method used for domain decomposition and (2) the Advancing Front (AF) method used for mesh generation. Starting from the surface mesh of the computational domain, the AP method is applied recursively to generate a set of sub-domains. Next, the sub-domains are meshed in parallel using the AF method. The recursive nature of domain decomposition naturally maps to a divide-and-conquer algorithm which exhibits inherent parallelism. For the parallel implementation, the Master/Worker pattern is employed to dynamically balance the varying workloads of each task on the set of available CPUs. Performance results by this approach are presented and discussed in detail as well as future work and improvements.
The development of and results obtained with a variable resolution stretched-grid GCM for the regional climate simulation mode, are presented. A global variable resolution stretched- grid used in the study has enhanced horizontal resolution over the U.S. as the area of interest The stretched-grid approach is an ideal tool for representing regional to global scale interaction& It is an alternative to the widely used nested grid approach introduced over a decade ago as a pioneering step in regional climate modeling. The major results of the study are presented for the successful stretched-grid GCM simulation of the anomalous climate event of the 1988 U.S. summer drought- The straightforward (with no updates) two month simulation is performed with 60 km regional resolution- The major drought fields, patterns and characteristics such as the time averaged 500 hPa heights precipitation and the low level jet over the drought area. appear to be close to the verifying analyses for the stretched-grid simulation- In other words, the stretched-grid GCM provides an efficient down-scaling over the area of interest with enhanced horizontal resolution. It is also shown that the GCM skill is sustained throughout the simulation extended to one year. The developed and tested in a simulation mode stretched-grid GCM is a viable tool for regional and subregional climate studies and applications.
The simulation of ice sheet‐climate interactions, such as surface mass balance fluxes, is sensitive to model grid resolution. Here we simulate the multi‐century evolution of the Greenland Ice Sheet (GrIS) and its interaction with the climate using the Community Earth System Model version 2.2 (CESM2.2) including an interactive GrIS component (the Community Ice Sheet Model v2.1 [CISM2.1]) under an idealized warming scenario (atmospheric CO 2 increases by 1% yr -1 until quadrupling the pre‐industrial level and then is held fixed). A variable‐resolution (VR) grid with 1/4° regional refinement over the broader Arctic and 1° resolution elsewhere is applied to the atmosphere and land components, and the results are compared with conventional 1° lat‐lon grid simulations to investigate the impact of grid refinement. Compared with the 1° runs, the VR run features a slower rate of surface melt, especially over the western and northern GrIS, where the ice surface slopes gently toward the periphery. This difference pattern originates primarily from higher snow albedo and, thus, weaker albedo feedback in the VR run. The VR grid better captures the CISM ice sheet topography by reducing elevation discrepancies between CAM and CISM and is, therefore, less reliant on the downscaling algorithm, which is known to underestimate albedo gradients. The sea level rise contribution from the GrIS in the VR run is 53 mm by year 150 and 831 mm by year 350, approximately 40% and 20% less than that of the 1° runs, respectively.
Radiation feedback plays a crucial role in the process of star formation. In order to simulate the thermodynamic evolution of disks, filaments, and the molecular gas surrounding clusters of young stars, we require an efficient and accurate method for solving the radiation transfer problem. We describe the implementation of a hybrid radiation transport scheme in the adaptive grid-based FLASH general magnetohydrodyanmics code. The hybrid scheme splits the radiative transport problem into a raytracing step and a diffusion step. The raytracer captures the first absorption event, as stars irradiate their environments, while the evolution of the diffuse component of the radiation field is handled by a flux-limited diffusion solver. We demonstrate the accuracy of our method through a variety of benchmark tests including the irradiation of a static disk, subcritical and supercritical radiative shocks, and thermal energy equilibration. We also demonstrate the capability of our method for casting shadows and calculating gas and dust temperatures in the presence of multiple stellar sources. Our method enables radiation-hydrodynamic studies of young stellar objects, protostellar disks, and clustered star formation in magnetized, filamentary environments.
Accelerator (accel) grid sputtering by ions formed through charge-exchange (CEX) reactions between beam ions and residual neutral gas is a critical life-limiting mechanism for gridded ion thrusters. The three-dimensional ion optics code CEX3D is designed to simulate this grid erosion for a single beamlet, with a particular emphasis on non-axisymmetric features such as the "pits and grooves" erosion commonly observed on the accel grid downstream face in two-grid thrusters. The treatment of CEX ions in the code was recently upgraded with a new particle-in-cell (PIC) module to account for the influence of these ions' space charge on the electrostatic potential downstream of the grids. In order to achieve reasonable computation times while resolving the Debye length near the grids and avoiding gross violations of the Courant-Friedrichs-Lewy (CFL) condition, macroparticle velocities in the PIC calculation are limited through a rescaling procedure that preserves ion trajectories and space charge density. The code accounts for beam divergence, finite momentum transfer in CEX collisions, and radial losses of CEX ions from the beam; these effects are important for determining the CEX ion flux to the accel grid because the calculated potential downstream of the grids can become very flat. The upgraded code has been used to simulate operation of NASA's Evolutionary Xenon Thruster (NEXT) during the 51 kHr Long Duration Test - a selection of results is presented and compared with experimental data.
The control point form of algebraic grid generation presented provides the means that are needed to generate well structured grids for turbomachinery flow simulations. It uses a sparse collection of control points distributed over the flow domain. The shape and position of coordinate curves can be adjusted from these control points while the grid conforms precisely to all boundaries. An interactive program called TURBO, which uses the control point form, is being developed. Basic features of the code are discussed and sample grids are presented. A finite volume LU implicit scheme is used to simulate flow in a turbine cascade on the grid generated by the program.
The control point form of algebraic grid generation presented provides the means that are needed to generate well structured grids of turbomachinery flow simulations. It uses a sparse collection of control points distributed over the flow domain. The shape and position of coordinate curves can be adjusted from these control points while the grid conforms precisely to all boundaries. An interactive program called TURBO, which uses the control point form, is being developed. Basic features of the code are discussed and sample grids are presented. A finite volume LU implicit scheme is used to simulate flow in a turbine cascade on the grid generated by the program.
Large simulation data requires a lot of time and computational resources to compute, store, analyze, visualize, and run user studies. Today, the largest cost of a supercomputer is not hardware but maintenance, in particular energy consumption. Our goal is to balance energy consumption and cognitive value of visualizations of resulting data. This requires us to go through the entire processing pipeline, from simulation to user studies. To reduce the amount of resources, data can be sampled or compressed. While this adds more computation time, the computational overhead is negligible compared to the simulation time. We built a processing pipeline at the example of regular sampling. The reasons for this choice are two-fold: using a simple example reduces unnecessary complexity as we know what to expect from the results. Furthermore, it provides a good baseline for future, more elaborate sampling methods. We measured time and energy for each test we did, and we conducted user studies in Amazon Mechanical Turk (AMT) for a range of different results we produced through sampling.
A grid block transformation scheme which allows the input of grids in arbitrary reference frames, the use of mirror planes, and grids with relative velocities has been developed. A simple ice crystal and sand particle bouncing scheme has been included.. Added an SLD splashing model based on that developed by William Wright for the LEWICE 3.2.2 software. A new area based collection efficiency algorithm will be incorporated which calculates trajectories from inflow block boundaries to outflow block boundaries. This method will be used for calculating and passing collection efficiency data between blade rows for turbo-machinery calculations.
Designing and planing next generation power grid sys- tems composed of large power distribution networks, monitoring and control networks, autonomous generators and consumers of power requires advanced simulation infrastructures. The objective is to predict and analyze in time the behavior of networks of systems for unexpected events such as loss of connectivity, malicious attacks and power loss scenarios. This ultimately allows one to answer questions such as: “What could happen to the power grid if ...”. We want to be able to answer as many questions as possible in the shortest possible time for the largest possible systems. In this paper we present a new High Performance Computing (HPC) oriented simulation infrastructure named Next Generation Network and System Simulator (NGNS2 ). NGNS2 allows for the distribution of a single simulation among multiple computing elements by using MPI and OpenMP threads. NGNS2 provides extensive configuration, fault tolerant and load balancing capabilities needed to simulate large and dynamic systems for long periods of time. We show the preliminary results of the simulator running approximately two million simulated entities both on a 64-node commodity Infiniband cluster and a 48-core SMP workstation.
Mesoscale research and forecast models are increasingly being used at horizontal resolutions of 1-8 km to simulate a variety of precipitating systems. When the model is used to simulate convective systems, it is uncertain to what extent the dynamics and microphysics of convective updrafts can be resolved with grids larger than 1 km. In this study, two- and three-dimensional versions of the Goddard Cumulus Ensemble model are used to determine the impact of horizontal grid resolution on the behavior of the simulated storms and on the characteristics of the cloud microphysical fields. It will be shown that as resolution decreases from about 1 km to greater than 3 km, there is a fairly rapid degradation of the storm structure in the form of reduced convective mass fluxes, updraft tilts, and cloud microphysics. A high-resolution simulation of hurricane outer rainbands using the MM5 mesoscale model shows also that there can be a substantial modification of the key microphysical processes that contribute to rainfall as a result of reducing the horizontal resolution.
Numerical simulations have been performed for a partially-dressed, cavity-closed nose landing gear configuration that was tested in NASA Langley s closed-wall Basic Aerodynamic Research Tunnel (BART) and in the University of Florida's open-jet acoustic facility known as the UFAFF. The unstructured-grid flow solver FUN3D, developed at NASA Langley Research center, is used to compute the unsteady flow field for this configuration. Starting with a coarse grid, a series of successively finer grids were generated using the adaptive gridding methodology available in the FUN3D code. A hybrid Reynolds-averaged Navier-Stokes/large eddy simulation (RANS/LES) turbulence model is used for these computations. Time-averaged and instantaneous solutions obtained on these grids are compared with the measured data. In general, the correlation with the experimental data improves with grid refinement. A similar trend is observed for sound pressure levels obtained by using these CFD solutions as input to a FfowcsWilliams-Hawkings noise propagation code to compute the farfield noise levels. In general, the numerical solutions obtained on adapted grids compare well with the hand-tuned enriched fine grid solutions and experimental data. In addition, the grid adaption strategy discussed here simplifies the grid generation process, and results in improved computational efficiency of CFD simulations.
Solids mixing affects thermal and concentration gradients in fluidized bed reactors and is, therefore, critical to their performance. Despite substantial effort over the past decades, understanding of solids mixing continues to be lacking because of technical limitations of diagnostics in large pilot and commercial‐scale reactors. This study is focused on investigating mixing dynamics and their dependence on operating conditions using computational fluid dynamics simulations. Toward this end, fine‐grid 3D simulations are conducted for the bubbling fluidization of three distinct Geldart B particles (1.15 mm LLDPE, 0.50 mm glass, and 0.29 mm alumina) at superficial gas velocities U/Umf = 2–4 in a pilot‐scale 50 cm diameter bed. The Two‐Fluid Model (TFM) is employed to describe the solids motion efficiently while bubbles are detected and tracked using MS3DATA. Detailed statistics of the flow‐field in and around bubbles are computed and used to describe bubble‐induced solids micromixing: solids upflow driven in the nose and wake regions while downflow along the bubble walls. Further, within these regions, the hydrodynamics are dependent only on particle and bubble characteristics, and relatively independent of the global operating conditions. Based on this finding, a predictive mechanistic, analytical model is developed which integrates bubble‐induced micromixing contributions over their size and spatial distributions to describe the gross solids circulation within the fluidized bed. Finally, it is shown that solids mixing is affected adversely in the presence of gas bypass, or throughflow, particularly in the fluidization of heavier particles. This is because of inefficient gas solids contacting as 30–50% of the superficial gas flow escapes with 2–3× shorter residence time through the bed. This is one of the first large‐scale studies where both the gas (bubble) and solids motion, and their interaction, are investigated in detail and the developed framework is useful for predicting solids mixing in large‐scale reactors as well as for analyzing mixing dynamics in complex reactive particulate systems. © 2017 American Institute of Chemical Engineers AIChE J , 63: 4316–4328, 2017
The first section is on 3-D numerical modeling of terrain-induced circulations and covers the following: (1) additional insights into gravity wave generation mechanisms based on the control simulation; (2) ongoing nested-grid numerical simulations; (3) work to be completed during the remainder of FY-93; and (4) work objectives for FY-94. The second section is on linear theory and theoretical modeling and covers the following: (1) the free response of a uniform barotropic flow to an initially stationary unbalanced (ageostrophic) zonal wind anomaly; and (2) the free response of a uniform barotropic flow to an initially stationary balanced zonal wind anomaly.
The goal of our research is to produce a flexible, general grid generator for automated use by other programs, such as numerical optimizers. The current trend in the gridding field is toward interactive gridding. Interactive gridding more readily taps into the spatial reasoning abilities of the human user through the use of a graphical interface with a mouse. However, a sometimes fruitful approach to generating new designs is to apply an optimizer with shape modification operators to improve an initial design. In order for this approach to be useful, the optimizer must be able to automatically grid and evaluate the candidate designs. This paper describes and intelligent gridder that is capable of analyzing the topology of the spatial domain and predicting approximate physical behaviors based on the geometry of the spatial domain to automatically generate grids for computational fluid dynamics simulators. Typically gridding programs are given a partitioning of the spatial domain to assist the gridder. Our gridder is capable of performing this partitioning. This enables the gridder to automatically grid spatial domains of wide range of configurations.
In developing the automated methodologies for simulation-based optimal shape designs, their accuracy, efficiency and practicality are the defining factors to their success. To that end, four recent improvements to the building blocks of such a methodology, intended for more practical design optimization, have been reported. First, in addition to a polynomial-based parameterization, a partial differential equation (PDE) based parameterization was shown to be a practical tool for a number of reasons. Second, an alternative has been incorporated to one of the tedious phases of developing such a methodology, namely, the automatic differentiation of the computer code for the flow analysis in order to generate the sensitivities. Third, by extending the methodology for the thin-layer Navier-Stokes (TLNS) based flow simulations, the more accurate flow physics was made available. However, the computer storage requirement for a shape optimization of a practical configuration with the -fidelity simulations (TLNS and dense-grid based simulations), required substantial computational resources. Therefore, the final improvement reported herein responded to this point by including the alternating-direct-implicit (ADI) based system solver as an alternative to the preconditioned biconjugate (PbCG) and other direct solvers.
Power grids worldwide are undergoing an unprecedented transition as a result of grid evolution meeting information revolution. The grid evolution is largely driven by the desire for green energy. Emerging grid technologies such as renewable generation, smart loads, plug-in hybrid vehicles, and distributed generation provide opportunities to generate energy from green sources and to manage energy use for better system efficiency. With utility companies actively deploying these technologies, a high level of penetration of these new technologies is expected in the next 5-10 years, bringing in a level of intermittency, uncertainties, and complexity that the grid did not see nor design for. On the other hand, the information infrastructure in the power grid is being revolutionized with large-scale deployment of sensors and meters in both the transmission and distribution networks. The future grid will have two-way flows of both electrons and information. The challenge is how to take advantage of the information revolution: pull the large amount of data in, process it in real time, and put information out to manage grid evolution. Without addressing this challenge, the opportunities in grid evolution will remain unfulfilled. This transition poses grand challenges in grid modeling, simulation, and information presentation. The computational complexity of underlying power grid modeling and simulation will significantly increase in the next decade due to an increased model size and a decreased time window allowed to compute model solutions. High-performance computing is essential to enable this transition. The essential technical barrier is to vastly increase the computational speed so operation response time can be reduced from minutes to seconds and sub-seconds. The speed at which key functions such as state estimation and contingency analysis are conducted (typically every 3-5 minutes) needs to be dramatically increased so that the analysis of contingencies is both comprehensive and real time. An even bigger challenge is how to incorporate dynamic information into real-time grid operation. Today’s online grid operation is based on a static grid model and can only provide a static snapshot of current system operation status, while dynamic analysis is conducted offline because of low computational efficiency. The offline analysis uses a worst-case scenario to determine transmission limits, resulting in under-utilization of grid assets. This conservative approach does not necessarily lead to reliability. Many times, actual power grid scenarios are not studied, and they will push the grid over the edge and resulting in outages and blackouts. This chapter addresses the HPC needs in power grid analysis and operations. Example applications such as state estimation and contingency analysis are given to demonstrate the value of HPC in power grid applications. Future research directions are suggested for high performance computing applications in power grids to improve the transparency, efficiency, and reliability of power grids.