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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Optimizing Irregular Communication with Neighborhood Collectives and Locality-Aware Parallelism

Irregular communication often limits both the performance and scalability of parallel applications. Typically, applications individually implement irregular communication as point-to-point, and any optimizations are integrated directly into the application. As a result, these optimizations lack portability. It is difficult to optimize point-to-point messages within MPI, as the interface for single messages provides no information on the collection of all communication to be performed. However, the persistent neighbor collective API, released in the MPI 4 standard, provides an interface for portable optimizations of irregular communication within MPI libraries. This paper presents methods for implementing existing optimizations for irregular communication within neighborhood collectives, analyzes the impact of replacing point-to-point communication in existing codebases such as Hypre BoomerAMG with neighborhood collectives, and finally shows up to a 1.38x speedup on sparse matrix-vector multiplication communication within a BoomerAMG solve through the use of our optimized neighbor collectives. Here, the authors analyze three implementations of persistent neighborhood collectives for Alltoallv: an unoptimized wrapper of standard point-to-point communication, and two locality-aware aggregating methods. The second locality-aware implementation exposes an non-standard interface to perform additional optimization, and the authors present the additional 0.07x speedup from the extended interface. All optimizations are available in an open-source codebase, MPI Advance, which sits on top of MPI, allowing for optimizations to be added into existing codebases regardless of the system MPI install.

AMG↗
DOE OSTI2021

Visualization, understanding, and mitigation of process-induced-membrane irregularities in gas diffusion electrode-based polymer electrolyte membrane fuel cells

Polymer electrolyte membrane fuel cells (PEMFC) show substantial promise for their application in electric vehicles. For large-scale manufacturing of PEMFCs, roll-to-roll coated gas-diffusion-electrodes (GDE) offer certain advantages over other production pathways. Procedures including hot pressing and coating an ionomer overlayer may be necessary for this manufacturing pathway to enable a suitable catalyst layer/membrane interface. The same procedures may potentially introduce membrane irregularities, especially when thin membranes are used. Limited understanding exists regarding if and to what extent such irregularities impact PEMFC performance and lifetime, and therefore be considered defects. In this study, NREL's customized fuel cell hardware that enables quasi in-situ infrared (IR) thermography studies was utilized to visualize spatial hydrogen crossover and identify membrane irregularities that originated from the GDE-based MEA fabrication process. The structure of these membrane irregularities was investigated by scanning electron microscopy (SEM) and its impact on initial H2/air performance was determined. Accelerated stress testing (AST) revealed that these irregularities develop into failure point locations. These results were validated across many MEAs with identified process-induced membrane irregularities. By selecting specific gas diffusion media properties and by fine tuning the MEA hot pressing parameters, the formation of such membrane irregularities was mitigated.

08 HYDROGEN↗
DOE OSTI2021

Investigation of Small-Scale Electron Density Irregularities Observed by the Arase and Van Allen Probes Satellites Inside and Outside the Plasmasphere

In situ electron density profiles obtained from Arase in the night magnetic local time (MLT) sector and from RBSP-B covering all MLTs are used to study the small-scale density irregularities present in the plasmasphere and near the plasmapause. Electron density perturbations with amplitudes >10% from background density and with time-scales less than 30-min are investigated here as the small-scale density irregularities. The statistical survey of the density irregularities is carried out using nearly 2 years of density data obtained from RBSP-B and 4 months of data from Arase satellites. The results show that density irregularities are present globally at all MLT sectors and L-shells both inside and outside the plasmapause, with a higher occurrence at L > 4. The occurrence of density irregularities is found to be higher during disturbed geomagnetic and interplanetary conditions. The case studies presented here revealed: (1) The plasmaspheric density irregularities observed during both quiet and disturbed conditions are found to coexist with the hot plasma sheet population. (2) During quiet periods, the plasma waves in the whistler-mode frequency range are found to be modulated by the small-scale density irregularities, with density depletions coinciding well with the decrease in whistler intensity. Our observations suggest that different source mechanisms are responsible for the generation of density structures at different MLTs and geomagnetic conditions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Compiler and Runtime Approaches to Enable Large-Scale Irregular Programs. Final report, July 2013 - July 2019

While regular algorithms, characterized by operations on dense matrices and arrays, have long been the mainstay of scientific, high-performance computing, irregular algorithms, which feature unpredictable accesses to pointer-based data structures, are becoming increasingly common in high performance computing, arising in graph analysis, data mining and visualization, among other domains. Unfortunately, the defining characteristics of irregular applications, their dynamic, unpredictable, data-dependent access patterns and data layouts, make achieving high performance on large scale systems difficult. Scaling applications to peta- and exa-scale requires carefully controlling communication and data movement and placement, an inherently difficult task when access patterns and data layouts are unpredictable! Most irregular applications that attain high performance must be painstakingly hand-written and hand-tuned, with few common principles or paradigms uniting various implementations and easing future development. Despite the increasing importance of irregular applications, there is little programmer knowledge, and even less compiler ability, devoted to optimizing them. This project aims to solve these problems. By allowing programmers to write irregular applications in high level forms, with at most a few annotations highlighting key structural properties, programmers can focus on developing their algorithms and methods. The compiler and run-time system can take on the tedious task of optimizing the application for execution at large scales, and can automatically provide efficient implementations. This will provide portability and ease maintenance for existing irregular applications, but, more importantly, open up whole new domains of computational science to large-scale, high-performance simulation codes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Impact of electrode thick spot irregularities on polymer electrolyte membrane fuel cell initial performance

Polymer electrolyte membrane fuel cells have great potential for power generation in many applications, but to implement them on a larger scale, understanding of quality requirements, tolerances, and controls during manufacturing must improve. As part of this broad challenge, irregularities resulting from the membrane electrode assembly production process must be studied to determine if they impact the performance of the cell. One potential irregularity is a locally increased thickness of the coated or deposited electrode. In order to understand and provide insight into the impact of such irregularities, we intentionally created thick spots in the center of cathode electrodes. The thick spots fabricated by two different approaches were carefully characterized by optical microscopy, X-ray fluorescence spectroscopy and scanning electron microscopy (SEM). We found that the impact of the thick spots on the electrochemically active catalyst area and mass activity was minimal. However, specific electrode thick spot irregularities significantly impacted the mass transport properties of the cells. Based on SEM analysis, the likely cause of the performance drop is morphological changes associated with the creation of the thick spot irregularity. Spatial performance results obtained with a segmented cell system further indicated that the area of the performance impact exceeded that of the intentionally created thick spot.

25 ENERGY STORAGE↗
DOE OSTI2022

Colors of Irregular Satellites of Saturn with the Dark Energy Camera

We report g – r and r – i new colors for 21 Saturn Irregular Satellites; among them, four previously unreported. This is the highest number of Saturn Irregular satellites reported in a single survey. These satellites were measured by "stacking" their observations to increase their signal without trailing. This work describes a novel processing algorithm that enables the detection of faint sources under significant background noise and in front of a severely crowded field. Our survey shows these new color measurements of Saturn Irregular Satellites are consistent with other Irregular Satellites populations as found in previous works and reinforcing the observation that the lack of ultrared objects among the irregular satellites is a real feature that separates them from the trans-Neptunian objects (their posited source population).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

The Effect of Membrane Casting Irregularities on Initial Fuel Cell Performance

Membrane electrode assemblies (MEA) for polymer electrolyte membrane fuel cells (PEMFC) may possess as-manufactured non-uniformities in any of its constituent components. This article studies casting irregularities located within the PEM to understand their potential impact on MEA initial performance. Membrane material was cast on a lab-scale polymer casting line operating either within or at the boundaries of the process window. The resulting membrane material was either pristine in the former case, or, in the latter case, contained air bubbles, cracks, and other irregularities, ranging in size from about 0.6 to 3 mm. Spatial polarization experiments were conducted using a 121-channel segmented fuel cell system, and thermal imaging was performed subsequently to map hydrogen crossover to spatial performance. While total-cell polarization data was minimally impacted by the irregularities, the spatial diagnostics showed local performance impacts that, in operation over time, could cause degradation in performance or earlier failure of the MEA. Such impacts could lead to these irregularities being classified as defects, i.e., manufacturing variations that should be identified and not included in a fuel cell stack. Classification of irregularities as defects will ultimately assist the industry by contributing to the development of threshold detection limits for in-line quality control diagnostics.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2026

Effect of Density Irregularities on Radio Frequency Wave Propagation in Ionospheric Plasmas

Density irregularities play a vital role in determining how radio frequency (RF) waves travel through plasmas. In the Earth’s ionosphere, these density irregularities also impact radio communication. In this study, we conduct a detailed numerical analysis of RF wave propagation in small-scale ionospheric density irregularities using the advanced Petra-M code. We focus specifically on high-frequency (HF) waves, ranging from 3 to 30 MHz, which are essential for military, amateur radio operators, and emergency communications. By introducing density structures, such as equatorial plasma bubbles derived from fluid simulations, we demonstrate that HF waves can scatter in multiple directions when they encounter these irregularities. Additionally, we observe significant mode conversion, where incoming electromagnetic waves transform into electrostatic modes within the density gradient layer. This shows that smaller density irregularities can greatly weaken signals or cause complete signal loss for receivers, emphasizing the need for increased awareness and innovative solutions in radio communication transmission.

Kim, Eun-Hwa [Princeton Plasma Physics Laboratory ↗
DOE OSTI2022

Near-field radiative heat transfer between irregularly shaped dielectric particles modeled with the discrete system Green's function method

Near-field radiative heat transfer (NFRHT) between irregularly shaped dielectric particles made of SiO 2 and morphology characterized by Gaussian random spheres is studied. Particles are modeled using the discrete system Green's function (DSGF) approach, which is a volume integral numerical method based on fluctuational electrodynamics. This method is applicable to finite, three-dimensional objects, and all system interactions are defined independent of thermal excitation by a generalized system Green's function. The DSGF method is deemed suitable to model NFRHT between irregularly shaped particles after verification against the analytical solution for chains of two and three SiO 2 spheres. The NFRHT results reveal that geometric irregularity in particles leads to a reduction of the total conductance from that of comparable perfect spheres at vacuum separation distances smaller than the particle size, a regime in which NFRHT is a surface phenomenon. At vacuum separation distances larger than the particle size, NFRHT becomes a volumetric process, and the total conductance between irregularly shaped particles converges to that of comparable perfect spheres. Spectral analysis reveals, however, that particle irregularity leads to damping and broadening of resonances at all separation distances, thereby highlighting the importance of the DSGF method for spectral engineering in the near field. The reduced spectral coherence when particle size is larger than the vacuum separation distance is attributed to coupling of surface phonon-polaritons within the randomly generated, distorted particle features. For particle size smaller than the vacuum separation distance, resonance broadening and damping are linked with the multiple localized surface phonon modes supported by the composite spherical harmonic morphologies of the Gaussian random spheres. In conclusion, this paper has direct implications for thermal management of packed particle systems, with applications in radiative property control, electronics, energy conversion, and nanomanufacturing.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

A Block-Structured Adaptive Mesh Framework to Solve Radiation Transfer Equation in Irregular Embedded Geometries

Radiation transport arises in various scientific, industrial, and medical fields, and understanding its effect in applications is needed to make accurate predictions, safety assessments and performance optimizations. Solving the Radiation Transport Equation (RTE) is challenging due to its integro-differential nature, which involves both differential and integral terms. The differential term describes the change in radiation intensity due to absorption and emission, while the integral term accounts for scattering. The accurate modeling of radiation is further complicated in many applications due to the complex, irregular geometries. Various methods exist for solving the RTE, including the zonal, Monte Carlo, spherical harmonics, discrete ordinates, and finite volume methods. Traditional mesh-based approaches, which rely on structured or unstructured meshes, struggle with irregular geometries due to: a) the difficulty of conforming structured grids to irregular domains, b) challenges in enforcing boundary conditions correctly, and c) the additional computational cost of unstructured mesh methods. This work presents a second-order accurate method for solving the RTE in irregular geometries. The radiation intensity is discretized using the finite-volume method in both spatial and angular directions on regular Cartesian grid blocks. Leveraging the block-structured adaptive mesh refinement (AMR) framework provided by AMReX, our method refines the grid locally to reduce spatial discretization error, ensuring a converged numerical solution while minimizing computational costs elsewhere. A two-stage deferred correction approach is employed: First, a first-order discretization on grid blocks is solved using an algebraic multigrid method in HYPRE. Second, a correction term is applied explicitly to achieve second-order accuracy. The correction term is calculated by approximating the radiation flux on cell faces using a Total Variation Diminishing (TVD) scheme. This approach ensures quick convergence of the multigrid method while preserving higher-order accuracy of the numerical solution. Irregular geometries are resolved as embedded boundaries (EB), resulting in both cut cells and regular cells. In cut cells, we modify the fluxes using face fractions and incorporate additional contributions from EB boundary conditions. To ensure higher-order convergence near the EB interface, the correction term is modified by interpolating the radiation intensity to fictitious ghost points. The implementation takes advantage of modern supercomputers by leveraging AMReX’sMPI/X parallelization strategy where X can be MPI or a GPU accelerator including CUDA, HIP and DPC++. We validate our solver using classical test cases, both with and without EB, demonstrating accuracy and efficiency. Additionally, we analyze the impact of adaptive mesh refinement on solution accuracy and computational cost, highlighting the advantages of our approach for high-resolution radiation transport simulations.

computational fluid dynamics (CFD)↗
DOE OSTI2022

Micromechanical Fields Associated with Irregular Deformation Twins in Magnesium

Understanding and controlling the development of deformation twins is paramount for engineering strong and stable hexagonal close-packed (HCP) Mg alloys. Actual twins are often irregular in boundary morphology and twin crystallography, deviating from the classical picture commonly used in theory and simulation. In this work, the elastic strains and stresses around irregular twins are examined both experimentally and computationally to gain insight into how twins develop and the microstructural features that influence their development. A nanoprecession electron diffraction (N-PED) technique is used to measure the elastic strains within and around a $\left\{ {10\overline{1}2} \right\}$ tensile twin in AZ31B Mg alloy with nm scale resolution. A full-field elasto-viscoplastic fast Fourier transform (EVP-FFT) crystal plasticity model of the same sub-grain and irregular twin structure is employed to understand and interpret the measured elastic strain fields. The calculations predict spatially resolved elastic strain fields in good agreement with the measurement, as well as all the stress components and the dislocation density fields generated by the twin, which are not easily obtainable from the experiment. The model calculations find that neighboring twins, several twin thicknesses apart, have little influence on the twin-tip micromechanical fields. Furthermore, this work reveals that irregularity in the twin-tip shape has a negligible effect on the development of the elastic strains around and inside the twin. Importantly, the major contributor to these micromechanical fields is the alignment of the twinning shear direction with the twin boundary.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Solution Irregularity Remediation for Spatial Discretization Error Estimation for S N Transport Solutions

The discrete ordinates linear Boltzmann transport equation is typically solved in its spatially discretized form, incurring spatial discretization error. Quantification of this error for purposes such as adaptive mesh refinement or error analysis requires an a posteriori estimator, which utilizes the numerical solution to the spatially discretized equation to compute an estimate. Because the quality of the numerical solution informs the error estimate, irregularities, present in the true solution for any realistic problem configuration, tend to cause the largest deviation in the error estimate vis-a-vis the true error. In this paper, an analytical partial singular characteristic tracking (pSCT) procedure for reducing the estimator’s error is implemented within our novel residual source estimator for a zeroth-order discontinuous Galerkin scheme, at the additional cost of a single inner iteration. Here, a metric-based evaluation of the pSCT scheme versus the standard residual source estimator is performed over the parameter range of a Method of Manufactured Solutions test suite. The pSCT scheme generates near-ideal accuracy in the estimate in problems where the dominant source of the estimator’s error is the solution irregularity, namely, problems where the true solution is discontinuous and problems where the true solution’s first derivative is discontinuous and the scattering ratio is low. In problems where the scattering ratio is high and the true solution is discontinuous in the first derivative, the error in the scattering source, which is not converged by the pSCT scheme, is greater than the error incurred due to the irregularity. Ultimately, a pSCT scheme is judged to be useful for error estimation in problems where the computational cost of the scheme is justified. In the presence of many irregularities, such a scheme may be intractable for general use, but in benchmarks, as an analytical tool, or in problems that have nondissipative discontinuities, the scheme may prove invaluable.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Coordinate-Based Seismic Interpolation in Irregular Land Survey: A Deep Internal Learning Approach

Physical and budget constraints often result in irregular sampling, which complicates accurate subsurface imaging. Preprocessing approaches, such as missing trace or shot interpolation, are typically employed to enhance seismic data in such cases. Recently, deep learning has been used to address the trace interpolation problem at the expense of large amounts of training data to adequately represent typical seismic events. Nonetheless, most research in this area has focused on trace reconstruction, with little attention having been devoted to shot interpolation. Furthermore, existing methods assume regularly spaced receivers/sources failing in approximating seismic data from real (irregular) surveys. This work presents a novel shot gather interpolation approach which uses a continuous coordinate-based representation of the acquired seismic wavefield parameterized by a neural network. The proposed unsupervised approach, which we call coordinate-based seismic interpolation (CoBSI), enables the prediction of specific seismic characteristics in irregular land surveys without using external data during neural network training. Importantly, experimental results on real and synthetic 3-D data validate the ability of the proposed method to estimate continuous smooth seismic events in the time-space and frequency-wavenumber domains, improving sparsity or low-rank-based interpolation methods.

58 GEOSCIENCES↗
DOE OSTI2024

From irregular to regular eutectic growth in the Al-Al 3 Ni system: In situ observations during directional solidification

Here we investigate the irregular eutectic growth dynamics of the Al-Al 3 Ni alloy, in which one of the solid phases (Al 3 Ni) grows faceted from the liquid. Leveraging in situ optical microscopy and synchrotron transmission x-ray microscopy, we address the question of the degree of coupling between Al and Al 3 Ni at the growth front and that of the shape of the microstructures left behind in the bulk solid during directional solidification. Real-time optical observations bring evidence for a morphological transition from a eutectic-grain dependent, irregular eutectic growth at low solidification velocity V (typically 1 μm s -1 ), to a weakly anisotropic, regular growth at higher V ( reaching 10 μm s -1 ). Unprecedented x-ray nano-imaging of the solid–liquid interface, and 3D characterization of the growth patterns, were made possible by a new DS setup at Brookhaven National Laboratory’s NSLS-II. At low V, the leading tips of partly faceted Al 3 Ni crystals are observed to grow not far ahead of the Al growth front. Correlating in situ images and postmortem 3D tomographic reconstructions reveals that the presence of faceted and non-faceted regions of Al 3 Ni crystals in the solid is a direct consequence of coupling and decoupling during DS, respectively. Upon increasing V, the lead distance of Al 3 Ni vanishes, and the shape of Al 3 Ni ceases to be governed by faceted growth. These observations cast light onto the basic mechanisms (faceted growth, diffusive coupling, and the dynamics of trijunctions) governing a faceted to rod-like transition upon increasing V in the Al 3 Ni system, with broad implications to a large class of irregular eutectics.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Discrete element modeling of granular hopper flow of irregular-shaped deformable particles

Many natural and engineered granular materials have relatively deformable particles. Besides particle size and shape, particle deformability is another salient factor that significantly impacts the material’s flow behavior. Here, in this work, the flow of irregular-shaped deformable particles in a wedge-shaped hopper is investigated using discrete element simulations. A bonded-sphere model is developed to simultaneously capture irregular particle shapes and particle-wise deformations (e.g., compression, deflection, and distortion). Quantitative analysis of the effects of irregular shapes and particle deformations shows that the increase in particle stiffness tends to increase initial packing porosity and decrease the flow rate in the hopper. Rigid particles tend to have clogging issues, whereas deformable particles have less chance to, indicating particle deformation reduces the critical bridging width in the hopper flow. Detailed analysis of stress fields is also conducted to provide insights into the mechanism of particle flow and clogging. Stresses and discharge rates calculated from numerical simulations are compared and show good agreement with Walker’s theory and the extended Beverloo formula. Simulations with various particle shape combinations are also performed and show that the initial packing porosity decreases with an increasing percentage of fibers while the discharge rate has a complex dependency on particle shapes.

09 BIOMASS FUELS↗
DOE OSTI2021

A Survey: Handling Irregularities in Neural Network Acceleration with FPGAs

In the last decade, Artificial Intelligence (AI) through Deep Neural Networks (DNNs) has penetrated virtually every aspect of science, technology, and business. Many types of DNNs have been and continue to be developed, including Convolutional Neural Networks (CNNs), Recurrent Neural Net- works (RNNs), and Graph Neural Networks (GNNs). The overall problem for all of these Neural Networks (NNs) is that their target applications generally pose stringent constraints on latency and throughput, while also having strict accuracy requirements. There have been many previous efforts in creating hardware to accelerate NNs. The problem designers face is that optimal NN models typically have significant irregularities, making them hardware-unfriendly. In this paper, we first define the problems in NN acceleration by characterizing common irregularities in NN processing into 4 types; then we summarize the existing works that handle the four types of irregularities efficiently using hardware, especially FPGAs; finally, we provide a new vision of next-generation FPGA-based NN acceleration: that the emerging heterogeneity in the next-generation FPGAs is the key to achieving higher performance.

Geng, Tong↗
DOE OSTI2023

An Efficient Three-Dimensional CFD-Based Numerical Wave Tank for a Wave Energy Converter in Extreme Irregular Waves

A numerical wave tank approach for computational fluid dynamics (CFD) modelling of an extreme irregular seastate is presented. The technique couples a potential flow solution with a CFD solver for more efficient numerical predictions. This method has recently become attractive both for the research community and the industry working with offshore structures. The model is used to determine the response of a submerged pressure differential wave energy converter (WEC) in a fully nonlinear irregular wave condition using the high-fidelity CFD code, STAR-CCM+. Potential flow based numerical models are commonly used to predict motions and performance of wave energy converters. Wave kinematics can deviate from potential flow predictions for extreme wave conditions; the excitation loads on an absorber can also be increasingly influenced by viscous effects, not predicted by potential flow engineering level models. In these extreme conditions, a Reynolds-averaged Navier-Stokes CFD model can better predict motions and loads for a WEC. Long time series with varying random seed numbers can be used to identify singular extreme wave events from a stochastic irregular sea state. This approach simulates a more realistic wave series for a given sea state than a regular wave or a focused wave. However, it is computationally infeasible to run these long time series for three-dimensional (3D) CFD simulations. In this work, two-dimensional (2D) CFD simulations with a long domain allow the full development of an extreme nonlinear wave condition. The results are used to identify extreme events from a 50-year storm condition for the PacWave site off the coast of Oregon. A relatively short time window including this extreme event is then mapped to a 3D simulation using a user defined wave methodology. Convergence studies for domain length, wave forcing lengths, and time before the extreme event were conducted.

CFD↗
DOE OSTI2023

An Efficient Three-Dimensional CFD-Based Numerical Wave Tank for a Wave Energy Converter in Extreme Irregular Waves: Preprint

A numerical wave tank approach for computational fluid dynamics (CFD) modelling of an extreme irregular seastate is presented. The technique couples a potential flow solution with a CFD solver for more efficient numerical predictions. This method has recently become attractive both for the research community and the industry working with offshore structures. The model is used to determine the response of a submerged pressure differential wave energy converter (WEC) in a fully nonlinear irregular wave condition using the high fidelity CFD code, STAR-CCM+. Potential flow based numerical models are commonly used to predict motions and performance of wave energy converters. Wave kinematics can deviate from potential flow predictions for extreme wave conditions; the excitation loads on an absorber can also be increasingly influenced by viscous effects, not captured in engineering level models. In these extreme conditions, a Reynolds-averaged Navier-Stokes CFD model can better predict motions and loads for a WEC. Long time series with varying random seed numbers can be used to identify singular extreme wave events from a stochastic irregular sea state. This approach simulates a more realistic wave series for a given sea state than a regular wave or a focused wave. However, it is computationally infeasible to run these long time series for three-dimensional (3D) CFD simulations. In this work, two-dimensional (2D) CFD simulations with a long domain allow the full development of an extreme nonlinear wave condition. The results are used to identify extreme events from a 50-year storm condition for the PacWave site off the coast of Oregon. A relatively short time window including this extreme event is then mapped to a 3D simulation using a user defined wave methodology. Convergence studies for domain length, wave forcing lengths, and time before the extreme event were conducted.

cfd↗