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At least 1,351 records · Page 75

Machine learning analysis of high-repetition-rate two-dimensional Thomson scattering spectra from laser-produced plasmas

With the emergence of high-repetition-rate two-dimensional Thomson scattering (TS) measurements, improving spectral data analysis is a key area of interest. Here, we present a new way to derive the electron temperature and density of laser-driven blast waves in plasmas from their TS spectra with machine learning (ML). This analysis occurs in both the non-collective (α < 1) and collective (α > 1) scattering regimes with the goal of autonomously and more accurately determining T c and n e both where spectral data has been collected and to give the ability to predict these attributes in regions where data has not been collected. We introduce three ML models, one trained only on experimental data, one only on synthetic data, and one using transfer learning, and compare their speed and accuracy with the conventional TS inversion algorithms in the open source PlasmaPy python package.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A methodology to generate crystal-based molecular structures for atomistic simulations

Abstract We propose a systematic method to construct crystal-based molecular structures often needed as input for computational chemistry studies. These structures include crystal ‘slabs’ with periodic boundary conditions (PBCs) and non-periodic solids such as Wulff structures. We also introduce a method to build crystal slabs with orthogonal PBC vectors. These methods are integrated into our code, Los Alamos Crystal Cut ( LCC ), which is open source and thus fully available to the community. Examples showing the use of these methods are given throughout the manuscript.

42 ENGINEERING↗

Parallel simulation via SPPARKS of on-lattice kinetic and Metropolis Monte Carlo models for materials processing

Abstract SPPARKS is an open-source parallel simulation code for developing and running various kinds of on-lattice Monte Carlo models at the atomic or meso scales. It can be used to study the properties of solid-state materials as well as model their dynamic evolution during processing. The modular nature of the code allows new models and diagnostic computations to be added without modification to its core functionality, including its parallel algorithms. A variety of models for microstructural evolution (grain growth), solid-state diffusion, thin film deposition, and additive manufacturing (AM) processes are included in the code. SPPARKS can also be used to implement grid-based algorithms such as phase field or cellular automata models, to run either in tandem with a Monte Carlo method or independently. For very large systems such as AM applications, the Stitch I/O library is included, which enables only a small portion of a huge system to be resident in memory. In this paper we describe SPPARKS and its parallel algorithms and performance, explain how new Monte Carlo models can be added, and highlight a variety of applications which have been developed within the code.

36 MATERIALS SCIENCE↗

Characterizing structural features of two-dimensional particle systems through Voronoi topology

This paper introduces a new approach toward characterizing local structural features of two-dimensional particle systems. The approach can accurately identify and characterize defects in high-temperature crystals, distinguish a wide range of nominally disordered systems, and robustly describe complex structures such as grain boundaries. This paper also introduces two-dimensional functionality into the open-source software program VoroTop which automates this analysis. This software package is built on a recently-introduced multithreaded version of V ORO ++, enabling the analysis of systems with billions of particles on high-performance computer architectures.

36 MATERIALS SCIENCE↗

In situ tumor model for longitudinal in silico imaging trials

Abstract Objective.In this article, we introduce a computational model for simulating the growth of breast cancer lesions accounting for the stiffness of surrounding anatomical structures.Approach.In our model, ligaments are classified as the most rigid structures while the softer parts of the breast are occupied by fat and glandular tissues As a result of these variations in tissue elasticity, the rapidly proliferating tumor cells are met with differential resistance. It is found that these cells are likely to circumvent stiffer terrains such as ligaments, instead electing to proliferate preferentially within the more yielding confines of the breast’s soft topography. By manipulating the interstitial tumor pressure in direct proportion to the elastic constants of the tissues surrounding the tumor, this model thus creates the potential for realizing a database of unique lesion morphology sculpted by the distinctive topography of each local anatomical infrastructure. We modeled the growth of simulated lesions within volumes extracted from fatty breast models, developed by Graffet alwith a resolution of 50μm generated with the open-source and readily available Virtual Imaging Clinical Trials for Regulatory Evaluation (VICTRE) imaging pipeline. To visualize and validate the realism of the lesion models, we leveraged the imaging component of the VICTRE pipeline, which replicates the siemens mammomat inspiration mammography system in a digital format. This system was instrumental in generating digital mammogram (DM) images for each breast model containing the simulated lesions.Results.By utilizing the DM images, we were able to effectively illustrate the imaging characteristics of the lesions as they integrated with the anatomical backgrounds. Our research also involved a reader study that compared 25 simulated DM regions of interest (ROIs) with inserted lesions from our models with DM ROIs from the DDSM dataset containing real manifestations of breast cancer. In general the simulation time for the lesions was approximately 2.5 hours, but it varied depending on the lesion’s local environment.Significance.The lesion growth model will facilitate and enhance longitudinal in silico trials investigating the progression of breast cancer.

Engineering↗

Modeling of particle transport, neutrals and radiation in magnetically-confined plasmas with Aurora

In this work, we present Aurora, an open-source package for particle transport, neutrals and radiation modeling in magnetic confinement fusion plasmas. Aurora's modern multi-language interface enables simulations of 1.5D impurity transport within high-performance computing frameworks, particularly for the inference of particle transport coefficients. A user-friendly Python library allows simple interaction with atomic rates from the Atomic Data and Atomic Structure database as well as other sources. This enables a range of radiation predictions, both for power balance and spectroscopic analysis. We discuss here the superstaging approximation for complex ions, as a way to group charge states and reduce computational cost, demonstrating its wide applicability within the Aurora forward model and beyond. Aurora also facilitates neutral particle analysis, both from experimental spectroscopic data and other simulation codes. Leveraging Aurora's capabilities to interface SOLPS-ITER results, we demonstrate that charge exchange is unlikely to affect the total radiated power from the ITER core during high performance operation. Finally, we describe the ImpRad module in the one modeling framework for integrated task framework, developed to enable experimental analysis and transport inferences on multiple devices using Aurora.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

PICSAR-QED: a Monte Carlo module to simulate strong-field quantum electrodynamics in particle-in-cell codes for exascale architectures

Abstract Physical scenarios where the electromagnetic fields are so strong that quantum electrodynamics (QED) plays a substantial role are one of the frontiers of contemporary plasma physics research. Investigating those scenarios requires state-of-the-art particle-in-cell (PIC) codes able to run on top high-performance computing (HPC) machines and, at the same time, able to simulate strong-field QED processes. This work presents the PICSAR-QED library, an open-source, portable implementation of a Monte Carlo module designed to provide modern PIC codes with the capability to simulate such processes, and optimized for HPC. Detailed tests and benchmarks are carried out to validate the physical models in PICSAR-QED, to study how numerical parameters affect such models, and to demonstrate its capability to run on different architectures (CPUs and GPUs). Its integration with WarpX, a state-of-the-art PIC code designed to deliver scalable performance on upcoming exascale supercomputers, is also discussed and validated against results from the existing literature.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Hazma meets HERWIG4DM: precision gamma-ray, neutrino, and positron spectra for light dark matter

Herein we present a new open-source package, Hazma 2, that computes accurate spectra relevant for indirect dark matter searches for photon, neutrino, and positron production from vector-mediated dark matter annihilation and for spin-one dark matter decay. The tool bridges across the regimes of validity of two state of the art codes: Hazma 1, which provides an accurate description below hadronic resonances up to center-of-mass energies around 250 MeV, and Herwig4DM, which is based on vector meson dominance and measured form factors, and accurate well into the few GeV range. The applicability of the combined code extends to approximately 1.5 GeV, above which the number of final state hadrons off of which we individually compute the photon, neutrino, and positron yield grows exceedingly rapidly. We provide example branching ratios, particle spectra and conservative observational constraints from existing gamma-ray data for the well-motivated cases of decaying dark photon dark matter and vector-mediated fermionic dark matter annihilation. Finally, we compare our results to other existing codes at the boundaries of their respective ranges of applicability. Hazma 2 is freely available on GitHub athttps://github.com/LoganAMorrison/Hazma.

79 ASTRONOMY AND ASTROPHYSICS↗

3D full wave fast wave modeling with realistic HHFW antenna geometry and SOL plasma in NSTX-U

This paper reports the significant advancement of our ability to model and to understand how RF waves interact with the SOL plasma, by developing for the full torus 3D scrape-off layer (SOL) plasma simulation together with the antenna and core plasma in the NSTX-U device in HHFW frequency regime for a cold plasma model. The present paper extends the previous modeling (Bertelli et al 2020 AIP Conf. Proc. 2254 030001) to a full 3D device geometry including realistic antenna geometry in order to capture a more realistic experimental situation including the fully 3D wave field effects and the antenna plasma interaction in the SOL plasma, and, at the same time, resulting core wave propagation. Here, the central tool of the present work is the Petra-M code, which is a newly developed state-of-the-art generic electromagnetic simulation tool for modeling RF wave propagation based on MFEM (http://mfem.org), an open source scalable C++ finite element method library.

3D RF modeling↗

Systematic analysis of magnetic equilibrium reconstruction with eddy currents on LTX- β

Magnetic equilibrium reconstruction in the Lithium Tokamak Experiment-Beta (LTX-β) is complicated by strong eddy currents and toroidal asymmetries arising from its segmented, close-fitting conducting shell. In the earlier experiment LTX, these three-dimensional (3D) conductor effects significantly distorted diagnostic signals and challenged conventional axisymmetric reconstruction methods. In this work, we demonstrate that accurate plasma equilibria can be recovered on LTX-β by incorporating a small number of dominant eddy current modes derived from realistic conductor models. Using the open-source $\tt{TokaMaker}$ Grad–Shafranov solver, we reconstruct equilibria across a systematically selected set of LTX-β discharges and validate them against the legacy $\tt{PSI-Tri}$ hybrid 2D-3D code. Our results show that fully 2D $\tt{TokaMaker}$ reconstructions achieve significantly improved agreement with flux loop and Mirnov probe measurements, reducing total chi-squared fitting errors, especially during startup. Finally, we develop new hybrid 2D-3D $\tt{TokaMaker}$ reconstructions by integrating the $\tt{ThinCurr}$ 3D eddy current model, which we optimize for significant further reduction of chi-squared in most scenarios. These findings underscore the importance of realistic wall-current modeling in short-pulse tokamaks, and establish a physics-based reconstruction framework that is extensible to devices with complex passive structures and 3D wall interactions.

Grad–Shafranov solver↗

Feedforward equilibrium trajectory optimization with GSPulse

One of the common tasks required for designing new plasma scenarios or evaluating capabilities of a tokamak is to design the desired equilibria using a Grad-Shafranov (GS) equilibrium solver. However, most standard equilibrium solvers are time-independent and do not include dynamic effects such as plasma current flux consumption, induced vessel currents, or voltage constraints. Another class of tools, plasma equilibrium evolution simulators, do include time-dependent effects. These are generally structured to solve the forward problem of evolving the plasma equilibrium given feedback-controlled voltages. In this work, we introduce GSPulse, a novel algorithm for equilibrium trajectory optimization, that is more akin to a pulse planner than a pulse simulator. GSPulse includes time-dependent effects and solves the inverse problem: given a user-specified set of target equilibrium shapes, as well as limits on the coil currents and voltages, the optimizer returns trajectories of the voltages, currents, and achievable equilibria. This task is useful for scoping performance of a tokamak and exploring the space of achievable pulses. The computed equilibria satisfy both Grad-Shafranov force balance and axisymmetric circuit dynamics. The optimization is performed by restructuring the free-boundary equilibrium evolution equations into a form where it is computationally efficient to optimize the entire dynamic sequence. GSPulse can solve for hundreds of equilibria simultaneously within a few minutes. GSPulse has been validated against NSTX-U and MAST-U experiments and against SPARC feedback control simulations, and is being used to perform scenario design for SPARC. The computed trajectories can be used as feedforward inputs that are connected to the feedback controller to inform and improve feedback performance. The code for GSPulse is available open-source at github.com/jwai-cfs/GSPulse_public.

equilibrium↗

Process-based balance of system cost modeling for offshore wind power plants in the United States

This paper describes the development of a process-based and open-source balance of system cost model that provides the capability to evaluate both existing and novel offshore wind technologies. Individual design and installation steps are represented with bottom-up engineering models that compute times and costs associated with the process; furthermore, operational constraints are assigned to each process so that delays caused by weather and presence of marine mammals may be accounted for in the overall project timeline. The model structure, assumptions, inputs, and results are vetted with industry partners and compared against actual projects for validation. Installation times show reasonable agreement with real data. Project cost sensitivities are investigated to compute the system-level impact of different design choices. First, individual vessel efficiencies are computed for varying numbers of installation vessels and weather time series to show the diminishing returns of more than two feeder barges. Then, array cable capital costs and installation times are determined for a representative project with different turbine sizes. These values quantify the cost-benefit tradeoffs and show a net-cost savings of decreasing numbers of turbines, increased turbine spacing, and fewer turbine terminations. These results demonstrate that the balance of system model features the accuracy, functionality, and accessibility to serve as the foundation for a wide range of analyses to identify cost reduction potentials for offshore wind energy in the United States.

17 WIND ENERGY↗

ExaWind: A multifidelity modeling and simulation environment for wind energy

We introduce the open-source ExaWind modeling and simulation environment for wind energy. The primary physics codes of ExaWind are Nalu-Wind and OpenFAST. Nalu-Wind is a wind-focused computational fluid dynamics (CFD) code that is coupled to the whole-turbine simulation code OpenFAST. The ExaWind environment was created under U.S. Department of Energy funding to achieve the highest-fidelity simulations of wind turbines and wind farms to date, with the goal of enabling disruptive changes to turbine and plant design and operation. Innovation will be gleaned through better understanding of the complex flow dynamics in wind farms, including wake evolution and the impact of wakes on downstream turbines and turbulent flow from complex terrain. High-fidelity predictive simulations employ hybrid turbulence models, geometry/boundary-layer-resolving CFD meshes, atmospheric turbulence, nonlinear structural dynamics, and fluid-structure interaction. While there is an emphasis on very high-fidelity simulations (e.g., blade resolved with full fluid-structure coupling), the ExaWind environment supports lower-fidelity modeling capabilities including actuator-line and -disk methods. Important in the development of ExaWind codes is that the codes scale well on today's largest petascale supercomputers and on the next-generation platforms that will enable exascale computing.

17 WIND ENERGY↗

Overview of FLORIS updates

In this paper, we review updates made to the FLORIS (FLOw Redirection and Induction in Steady State) open-source framework for wind farm control modeling, design and analysis. The updates are focused on improvements for large arrays of turbines - including heterogenous inflows and incorporating second-order wake steering effects - design, and analysis tools for practical application of wind farm control, and improvements to the software architecture for best practices in modularization and cooperative development.

17 WIND ENERGY↗

Results from the FOCAL Experiment Campaign 1: Turbine Control Co-Design

This paper summarizes the scaling approach and results from the first experimental campaign of the Floating Offshore-wind and Controls Advanced Laboratory (FOCAL) Experimental Program, which is focused on developing public data sets to support the validation of numerical models for floating wind control co-design. A 1:70 Froude-scale performance-matched model of the IEA Wind 15-MW reference turbine was designed, built, and characterized on a fixed base. The National Renewable Energy Laboratory's Reference Open-Source COntroller (ROSCO) was integrated into the scale testing to examine the impact advanced turbine and generator control strategies have on turbine performance and loads, enabling validation of control strategies for floating wind design optimization.

17 WIND ENERGY↗

Aeroservoelastic Stability of a Floating Wind Turbine

The problem of negative damping undermines the aeroservoelastic stability of floating offshore wind turbines. The negative damping problem is most prevalent around rated wind speed, where the sensitivity of thrust to wind speed is the largest. This paper investigates the implementation of peak shaving, a controller feature that limits the rated thrust by pitching the blades before rated wind speed is reached. Two controller designs are investigated: a de-tuned controller and a nacelle-feedback controller. A time-domain metric is defined, inspired by Lyapunov theory, in order to compute and assess the stability of floating offshore wind turbines. The model of the International Energy Agency 15-MW reference wind turbine mounted on the University of Maine VolturnUS-S floater is simulated in HAWC2 with the National Renewable Energy Laboratory reference open-source controller. Peak shaving is applied to the two controller designs and stability is assessed. According to the chosen metric, peak shaving does not improve the stability of the system. This is due to the trade-off between loads and error tracking: although the loads and displacements in the fore-aft direction of the turbine are reduced, the rotor-speed tracking is poorer, which increases the shaft torsion fatigue load.

17 WIND ENERGY↗

Seabed bathymetry and friction modeling in MoorDyn

This paper presents the implementation and verification of a seabed bathymetry feature and seabed friction feature to the open-source, lumped-mass mooring system dynamics modeler, MoorDyn, which is part of the National Renewable Energy Laboratory’s aero-hydro-servo-elastic simulation tool, OpenFAST. Variations in seabed slope, as well as the frictional effects of mooring lines moving along the seabed, will affect the mooring line tensions of a floating platform and the consequent platform response. These new features are especially relevant for modeling mooring systems in deep-water coastal areas where seabed depth can change significantly over an entire mooring footprint. The bathymetry feature models the seabed as a rectangular grid of variable water depths in place of the existing, uniform water depth in MoorDyn. The friction force is primarily represented as a Coulombic friction force, or the product of a kinetic friction coefficient and the seabed contact normal force, with the ability to differentiate between transverse and axial motion of a line node on the seabed in any bathymetry grid. These capabilities were tested by running MoorDyn and OpenFAST simulations over a variety of seabed and environmental conditions; the resulting fairlead tensions, node tensions, and mooring line kinematics were verified against equivalent OrcaFlex simulations. The results match closely, meaning the features are verified, which will increase the overall fidelity of OpenFAST and FAST.Farm simulations.

17 WIND ENERGY↗

Progress toward Accelogic compression in ROOT

For the last 7 years, Accelogic pioneered and perfected a radically new theory of numerical computing codenamed “Compressive Computing”, which has an extremely profound impact on real-world computer science [1]. At the core of this new theory is the discovery of one of its fundamental theorems which states that, under very general conditions, the vast majority (typically between 70% and 80%) of the bits used in modern large-scale numerical computations are absolutely irrelevant for the accuracy of the end result. This theory of Compressive Computing provides mechanisms able to identify (with high intelligence and surgical accuracy) the number of bits (i.e., the precision) that can be used to represent numbers without affecting the substance of the end results, as they are computed and vary in real time. The bottom-line outcome will be to provide state-of-the-art compression algorithms --and accompanying software libraries-- able to surpass the performance of the compression engines currently available in the ROOT [7] framework. The resulting technology has the capability to enable substantial economic and operational gains (including speedup) for High Energy and Nuclear Physics data storage/analysis. In our initial studies, a factor of nearly x4 (3.9) compression was achieved with RHIC/STAR data where ROOT compression managed only x1.4 [6].As a collaboration of experimental scientists, private industry, and the ROOT Team, our aim is to capitalize on the substantial success delivered by the initial effort and produce a robust technology properly packaged as an open-source tool that could be used by virtually every experiment around the world as means for improving data management and accessibility.In this contribution, we will present our efforts integrating our concepts of “functionally lossless compression” within the ROOT framework implementation, with the purpose of producing a basic solution readily integrated into HENP applications. We will also present our progress applying this compression through realistic examples of analysis from both the STAR and CMS experiments.

Canal, Ph.↗