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At least 937 records · Page 52

Data-Driven RANS Turbulence Closures for Forced Convection Flow in Reactor Downcomer Geometry

Recent progress in data-driven turbulence modeling has shown its potential to enhance or replace traditional equation-based Reynolds-averaged Navier-Stokes (RANS) turbulence models. Here, this work utilizes invariant neural network (NN) architectures to model Reynolds stresses and turbulent heat fluxes in forced convection flows (when the models can be decoupled). As the considered flow is statistically one dimensional, the invariant NN architecture for the Reynolds stress model reduces to the linear eddy viscosity model. To develop the data-driven models, direct numerical and RANS simulations in vertical planar channel geometry mimicking a part of the reactor downcomer are performed. Different conditions and fluids relevant to advanced reactors (sodium, lead, unitary-Prandtl-number fluid, and molten salt) constitute the training database. The models enabled accurate predictions of velocity and temperature, and compared to the baseline k–τ turbulence model with the simple gradient diffusion hypothesis, do not require tuning of the turbulent Prandtl number. The data-driven framework is implemented in the open-source graphics processing unit–accelerated spectral element solver nekRS and has shown the potential for future developments and consideration of more complex mixed convection flows.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Altered morphology and diffusivity of water confined in MXenes: Machine learning–accelerated computations combined with experiments

Nanoconfined water exhibits unique properties compared to bulk water due to limited quantities, frustrated hydrogen bonding, and surface interactions, which are fundamental for energy storage and transport applications. We integrate machine learning–accelerated ab initio molecular dynamics with x-ray diffraction (XRD) and inelastic neutron scattering (INS) to systematically analyze the thermodynamic and dynamic behavior of water confined between functionalized (-F, -O, and -OH) two-dimensional (2D) Ti 3 C 2 T x MXene layers. As water intercalates between layers, the interlayer spacing exhibits layer-dependent staging characteristics. The water polarization can be flipped by the count and morphology of intercalated molecules interacting with MXene surface groups, resulting in varying electrostatic potential profiles. On the basis of interfacial electrostatic potential, hydrogen bond lifetime, and molecular orientation, we establish a linear combination of exponential model describing water diffusivity. These computational insights align well with experimental x-ray and neutron measurements, suggesting strategies for tuning water morphology and transport by tailoring MXene surface chemistry and water content for electrochemical energy storage and nanofluidic applications.

Tang, Jiawei [Southeast Univ., Nanjing (China)] (O↗

The cyclotron gas stopper at FRIB getting ready for operations

Linear gas stopping cells have been used for nearly two decades to slow down projectile fragments at the National Superconducting Cyclotron Laboratory, now the Facility for Rare Isotope Beams, for experiments with low-energy and reaccelerated beams. In order to efficiently stop and rapidly extract light to medium-mass fast ions, a cyclotron gas-stopper has been constructed. It uses a cyclotron-type magnet and a helium-gas filled stopping chamber to slow down the injected beam. RF ion guides transport the stopped ions to the center of the magnet and axially through the bore before acceleration to <60 keV. Following successful offline tests, the cyclotron stopper was moved to an experimental vault and connected to a new momentum–compression beam line. Beam transport to and into the cyclotron stopper was tested with stable beams. Finally, using 46 K fragments, the first successful stopping and extraction of a high-energy beam with the cyclotron stopper was demonstrated.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Inverse modeling of circular lattices via orbit response measurements in the presence of degeneracy

The number and location of beam position monitors (BPMs) and steerers with respect to the quadrupoles in a circular lattice can lead to degeneracy in the context of fitting linear optics and extracting lattice information from measured closed orbits. Furthermore, the measurement uncertainties due to the imperfection of BPMs and steerers can be propagated by the fitting process in ways that prohibit the successful extraction of discrepancies between lattice elements in the real machine and their description in the corresponding model. We systematically studied the influence of the placement of BPMs and steerers on the reconstruction of linear optics and corresponding lattice information. The derivative of orbit response coefficients with respect to the quadrupole strengths, the Jacobian, is derived as an analytical formula. This analytical version of the Jacobian is used to further derive the theoretical limitations of fitting linear optics from closed orbits in terms of the placement of BPMs and steerers. It is further demonstrated that when evaluating the Jacobian during the fitting procedure, the analytical version can be used in place of the conventional finite-difference computation. This allows for greatly improved efficiency when computing the Jacobian during each iteration of the fitting procedure. The approach is tested with large-scale simulations and the findings are verified by measurement data taken on SIS18 synchrotron at GSI Helmholtz Centre for Heavy Ion Research. The presented methods are of general nature and can be applied to other accelerator lattices as well. The fitting procedure by using the analytical Jacobian is tested in conjunction with various methods for mitigating quasidegeneracy and the results agree with those obtained by using the conventional Jacobian via finite-difference approximation.

47 OTHER INSTRUMENTATION↗

Time-temperature-superposition analysis of diverse datasets by the minimum-arclength method: long-term prediction with uncertainty margins

In a recent publication, we carried out an extensive analysis of an unsupervised method of determining optimum shift factors in time-temperature-superposition of accelerated-aging data that involves minimizing the vertical arclength to obtain the master curve. For synthetic Arrhenius data with a variety of noise distributions, the work showed that, in conjunction with bootstrap-resampling, the method can produce reliable estimates of the mean activation energy along with uncertainty quantification. Here, we apply the above method to six different datasets taken from the published literature and demonstrate accurate prediction of mean activation energy from the data as-is without the need for any pre-processing or fitting. We also compare uncertainty margins computed by second-order bootstrap with that by linear regression theory and show that the former appears to provide consistent margins in the presence of common noise types in real data, including intra-isotherm measurement-errors, sample-to-sample variations, and intrinsic deviation from perfect Arrhenius behavior.

36 MATERIALS SCIENCE↗

Relations between Shot Noise, Gain Bandwidth, and Saturation of Instabilities

There are numerous instabilities present in charged particle beams that undergo exponential growth and reach saturation. In various applications, such as free-electron lasers or micro-bunching light sources, achieving saturation is desirable. Conversely, there are applications where these instabilities are utilized as linear broad-band amplifiers for signals embedded in the charged beam. In the latter scenario, the saturation of an instability induces non-linear distortions in the imprinted signal, thereby limiting the useful range of such amplifiers. Accurate evaluation of these instabilities necessitates a complete and comprehensive modeling approach that includes shot noise within the beam. Unfortunately, such modeling is not always feasible or practical. In this paper, we introduce a methodology utilizing the frequency and bandwidth of the instability as key parameters. Through this, we derive an estimation for the range of linear instability growth. Our derivation is conducted in a model-independent manner, making it applicable to a broad spectrum of instabilities. To validate our approach, we employ established and thoroughly benchmarked simulations with a free electron laser (FEL) code as well as self-consistent 3-dimensional simulation of plasma-cascade instability using code SPACE.

43 PARTICLE ACCELERATORS↗

Performance of the Fermilab Linac Injector

The Fermilab Linac injection line consists of a 35 keV magnetron-type H\textsuperscript{-} ion source, two-solenoid Low Energy Beam Transport (LEBT), 201 MHz 4-rod 750 keV Radio Frequency Quadrupole (RFQ), and a Medium Energy Transport (MEBT) containing 4 quadrupoles and a bunching cavity. The injector delivers 25 mA, 48 µs pulses to the drift-tube Linac at a repetition rate of 15Hz. The transmission efficiency of the injector has been lower than expected since commissioning. Recent beam current measurements suggest that the beam is primarily lost upstream of the RFQ exit. Numerical simulations indicate that ions passing through the non-linear field region of the solenoids could produce a beam with an increased emittance resulting in up to 50\% of the LEBT beam current failing to meet the RFQ acceptance. An aperture restriction was installed upstream of the first solenoid to remove these ions. This report describes the results of measurements and simulations as well as the LEBT tuning.

43 PARTICLE ACCELERATORS↗

A Fast Flexibility-Driven Generation Portfolio Planning Method for Sustainable Power Systems

We are witnessing an acceleration in the uptake of renewable energy in power systems. Because of the associated variability and uncertainty of renewables, power systems need to have an adequate supply of flexibility to allow for suitable management of short-term operations. So far most of the work in this area has neglected how flexibility needs associated with renewables are fulfilled as part of dispatchable generation capital investments decisions. To address this challenge, we propose an approach to plan the dispatchable generation mix of a power system as needed to counteract variability and uncertainty associated with significant shares of variable renewable generation. The approach exploits the linear time-invariant feature of variable generation variability using historical phase planes of capacity (in MW) and ramp (in MW/min) to bridge the gap between long-term capacity planning and short-term intra-hour flexibility needs. This approach is much more computationally tractable than other proposals, while also being able to capture adequately short-term operational features like ramping and net load variability. Numerical tests are performed on realistic datasets to substantiate the effectiveness of the approach.

bulk power system planning↗

Evaluation of predictive correlation between flux expulsion and grain growth for superconducting radio frequency cavities

Abstract A series of experiments were carried out in an effort to develop a simple method for predicting the magnetic flux expulsion behavior of high purity niobium used to fabricate superconducting radio frequency (SRF) cavities. Using conventional metallographic characterizations in conjunction with high spatial resolution electron backscattered diffraction-orientation imaging microscopy, we find that the flux expulsion behavior of 1.3 GHz single cell SRF Nb cavities is significantly associated with the grain growth of the Nb material during heat treatment. Most of the Nb grains rapidly grew during 900 °C heat treatment, and were likely full-recrystallized with 1000 °C HT. When compared to the magnetic flux expulsion ratio ( B sc / B nc ) at Δ T = 5 K, the flux expulsion efficiency of the cavities increases with the increase of grain size. Most interestingly, 900 °C HT shows a roughly linear trend that suggests that this criterion could be used to predict the appropriate heat treatment temperature for sufficient flux expulsion behavior in SRF-grade Nb. This result can be used to see if flux expulsion can be predicted by examining the materials coming from Nb vendors, prior to cavity fabrication.

43 PARTICLE ACCELERATORS↗

A graphics processing unit accelerated sparse direct solver and preconditioner with block low rank compression

We present the GPU implementation efforts and challenges of the sparse solver package STRUMPACK. The code is made publicly available on github with a permissive BSD license. STRUMPACK implements an approximate multifrontal solver, a sparse LU factorization which makes use of compression methods to accelerate time to solution and reduce memory usage. Multiple compression schemes based on rank-structured and hierarchical matrix approximations are supported, including hierarchically semi-separable, hierarchically off-diagonal butterfly, and block low rank. Here, in this paper, we present the GPU implementation of the block low rank (BLR) compression method within a multifrontal solver. Our GPU implementation relies on highly optimized vendor libraries such as cuBLAS and cuSOLVER for NVIDIA GPUs, rocBLAS and rocSOLVER for AMD GPUs and the Intel oneAPI Math Kernel Library (oneMKL) for Intel GPUs. Additionally, we rely on external open source libraries such as SLATE (Software for Linear Algebra Targeting Exascale), MAGMA (Matrix Algebra on GPU and Multi-core Architectures), and KBLAS (KAUST BLAS). SLATE is used as a GPU-capable ScaLAPACK replacement. From MAGMA we use variable sized batched dense linear algebra operations such as GEMM, TRSM and LU with partial pivoting. KBLAS provides efficient (batched) low rank matrix compression for NVIDIA GPUs using an adaptive randomized sampling scheme. The resulting sparse solver and preconditioner runs on NVIDIA, AMD and Intel GPUs. Interfaces are available from PETSc, Trilinos and MFEM, or the solver can be used directly in user code. We report results for a range of benchmark applications, using the Perlmutter system from NERSC, Frontier from ORNL, and Aurora from ALCF. For a high frequency wave equation on a regular mesh, using 32 Perlmutter compute nodes, the factorization phase of the exact GPU solver is about 6.5× faster compared to the CPU-only solver. The BLR-enabled GPU solver is about 13.8× faster than the CPU exact solver. For a collection of SuiteSparse matrices, the STRUMPACK exact factorization on a single GPU is on average 1.9× faster than NVIDIA’s cuDSS solver.

97 MATHEMATICS AND COMPUTING↗

A Preliminary Feasibility Study on Multi-Cavity Cryomodule Integration for the Electron Ion Collider Energy Recover Linac Cooler

The Electron-Ion Collider (EIC) is a state-of-the-art accelerator designed for collisions between highly polarized electrons and ions. To achieve optimal luminosity, the ion beam is cooled using an electron beam sourced from an energy recovery linac (ERL). In the current ERL baseline design, one BNL type RF cavity is used per cryomodule, leading to spatial and cost challenges. This study examines the feasibility of using more compact PERLE (Powerful Energy Recovery Linac for Experiments) type cavities, which can house multiple cavities within a single cryomodule, by evaluating their Beam Breakup (BBU) instability performance. Higher Order Modes (HOM) parameters were obtained through frequency scaling, assuming constant quality factor Q_L, R/Q, and linearly scaling HOM frequencies. To predict the BBU threshold current and ensure accuracy, two different BBU tracking simulations are used for cross-verification. Although the reduced footprint of PERLE-type cavities is advantageous, maintaining sufficient damping of HOMs remains crucial. Finally, we compare the HOM damping efficiency of both cavity types and suggest a pathway forward.

Deitrick, K.↗

Bandgap tuning of two-dimensional materials by sphere diameter engineering

Developing a precise and reproducible bandgap tuning method that enables tailored design of materials is of crucial importance for optoelectronic devices. Towards this end, we report a sphere diameter engineering (SDE) technique to manipulate the bandgap of two-dimensional (2D) materials. A one-to-one correspondence with an ideal linear working curve is established between the bandgap of MoS 2 and the sphere diameter in a continuous range as large as 360 meV. Fully uniform bandgap tuning of all the as-grown MoS 2 crystals is realized due to the isotropic characteristic of the sphere. More intriguingly, both a decrease and an increase of the bandgap can be achieved by constructing a positive or negative curvature. By fusing individual spheres in the melted state, post-synthesis bandgap adjustment of the supported 2D materials can be realized. In conclusion, this SDE technique, showing good precision, uniformity and reproducibility with high efficiency, may further accelerate the potential applications of 2D materials.

36 MATERIALS SCIENCE↗

Quantum computing for fusion energy science applications

This is a review of recent research exploring and extending present-day quantum computing capabilities for fusion energy science applications. We begin with a brief tutorial on both ideal and open quantum dynamics, universal quantum computation, and quantum algorithms. Then, we explore the topic of using quantum computers to simulate both linear and nonlinear dynamics in greater detail. Because quantum computers can only efficiently perform linear operations on the quantum state, it is challenging to perform nonlinear operations that are generically required to describe the nonlinear differential equations of interest. In this work, we extend previous results on embedding nonlinear systems within linear systems by explicitly deriving the connection between the Koopman evolution operator, the Perron–Frobenius evolution operator, and the Koopman–von Neumann evolution (KvN) operator. We also explicitly derive the connection between the Koopman and Carleman approaches to embedding. Extension of the KvN framework to the complex-analytic setting relevant to Carleman embedding, and the proof that different choices of complex analytic reproducing kernel Hilbert spaces depend on the choice of Hilbert space metric are covered in the appendixes. Finally, we conclude with a review of recent quantum hardware implementations of algorithms on present-day quantum hardware platforms that may one day be accelerated through Hamiltonian simulation. We discuss the simulation of toy models of wave–particle interactions through the simulation of quantum maps and of wave–wave interactions important in nonlinear plasma dynamics.

Joseph, I. (ORCID:0000000255400840)↗

Data driven drift correction for complex optical systems

To exploit the thousand-fold increase in spectral brightness of modern light sources, increasingly intricate experiments are being conducted that demand extremely precise beam trajectory. Maintaining the optimal trajectory over several hours of an experiment with the needed precision necessitates active drift control. Here, we outline time varying Bayesian optimization (TVBO) as a data driven approach for robust drift correction, and illustrate its application for a split and delay optical system composed of six crystals and twelve input dimensions. Using numerical simulations, we exhibit the application of TVBO for linear drift, non-smooth temporal drift as well as constrained TVBO for multi-objective control settings, representing real-life operating conditions. This approach can be easily adapted to other X-ray beam conditioning and guidance systems, including multi-crystal monochromators and grazing-incidence mirrors, to maintain sub-micrometer and nanoradian beam stability over the course of an experiment spanning several hours.

Bayesian optimization↗

Mitigation of the Brighter-Fatter Effect in the LSST Camera

Thick, fully depleted charge-coupled devices (CCDs) are known to exhibit non-linear behavior at high signal levels due to the dynamic behavior of charges collecting in the potential wells of pixels, called the brighter-fatter effect (BFE). This particularly impacts bright calibration stars, which appear larger than their intrinsic shape, creating a flux-dependent point-spread function (PSF) that if left unmitigated, could make up a large fraction of the error budget in Stage IV weak-lensing (WL) surveys such as the Legacy Survey of Space and Time (LSST). In this paper, we analyze image measurements of flat fields and artificial stars taken at different illumination levels with the LSST Camera (LSSTCam) at SLAC National Accelerator Laboratory in order to quantify this effect in the LSST Camera before and after a previously introduced correction technique. We observe that the BFE evolves anisotropically as a function of flux due to higher-order BFEs, which violates the fundamental assumption of this correction method. We then introduce a new sampling method based on a physically motivated model to account these higher-order terms in the correction, and then we test the modified correction on both datasets. We find that the new method corrects the effect in flat fields better than it corrects the effect in artificial stars which we conclude is the result of a unmodeled curl component of the deflection field by the correction. We use these results to define a new metric for the full-well capacity of our sensors and advise image processing strategies to further limit the impact of the effect on LSST WL science pathways.

47 OTHER INSTRUMENTATION↗

Investigating the Role of Energy Density in Thermal Runaway of Lithium-Ion Batteries with Accelerating Rate Calorimetry

This work uses accelerating rate calorimetry to evaluate the impact of cell chemistry, state of charge, cell capacity, and ultimately cell energy density on the total energy release and peak heating rates observed during thermal runaway of Li-ion batteries. While the traditional focus has been using calorimetry to compare different chemistries in cells of similar sizes, this work seeks to better understand how applicable small cell data is to understand the thermal runaway behavior of large cells as well as determine if thermal runaway behaviors can be more generally tied to aspects of lithium-ion cells such as total stored energy and specific energy. We have found a strong linear correlation between the total enthalpy of the thermal runaway process and the stored energy of the cell, apparently independent of cell size and state of charge. We have also shown that peak heating rates and peak temperatures reached during thermal runaway events are more closely tied to specific energy, increasing exponentially in the case of peak heating rates.

25 ENERGY STORAGE↗

A fully implicit, scalable, conservative nonlinear relativistic Fokker–Planck 0D-2P solver for runaway electrons

Upon application of a sufficiently strong electric field, electrons break away from thermal equilibrium and approach relativistic speeds. These highly energetic ‘runaway’ electrons (~ MeV) play a significant role in tokamak disruption physics, and therefore their accurate understanding is essential to develop reliable mitigation strategies. As such, we have developed a fully implicit solver for the 0D-2P (i.e., including two momenta coordinates) relativistic nonlinear Fokker–Planck equation (rFP). As in earlier implicit rFP studies (NORSE, CQL3D), electron–ion interactions are modeled using the Lorentz operator, and synchrotron damping using the Abraham–Lorentz–Dirac reaction term. However, our implementation improves on these earlier studies by (1) ensuring exact conservation properties for electron collisions, (2) strictly preserving positivity, and (3) being scalable algorithmically and in parallel. Key to our proposed approach is an efficient multigrid preconditioner for the linearized rFP equation, a multigrid elliptic solver for the Braams–Karney potentials, and a novel adaptive technique to determine the associated boundary values. We verify the accuracy and efficiency of the proposed scheme with numerical results ranging from small electric-field electrical conductivity measurements to the accurate reproduction of runaway tail dynamics when strong electric fields are applied.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Single-particle dynamics of microbunching

The mechanism of steady-state microbunching (SSMB) has been proposed [D. F. Ratner and A. W. Chao, Phys. Rev. Lett. 105, 154801 (2010)] to generate high-power coherent radiation at a high repetition rate or in continuous-wave mode using electron storage rings. In this paper, the related single-particle dynamics are theoretically and numerically studied, and important results are presented. The investigated effects are longitudinal quantum radiation excitation, nonlinear momentum compaction, and linear and nonlinear coupling of the transverse and longitudinal motion. Although this analysis is oriented toward SSMB, some of the analyzed effects are also crucial in cases such as coherent harmonic generation, bunch slicing, bunch compression, free-electron laser beam transport lines, and quasi-isochronous rings, which involve precise longitudinal phase-space manipulations.

43 PARTICLE ACCELERATORS↗