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DOE OSTI2025

IER 516: Zirconium Test Assembly CED Phase-1: Preliminary Experiment Design

IER-516, Zirconium Test Assembly (ZTA), is a campaign to design, execute, and document a series of high-fidelity critical benchmark experiments to validate current and future zirconium (Zr) and zirconium hydride (ZrH x ) nuclear data evaluations. ZTA is a collaborative project between Los Alamos National Laboratory and the French Autoritè de Sûretè Nuclèaire et de Radioprotection. The experiments will be fueled with highly enriched uranium (HEU), and utilize the Comet critical assembly machine at the National Criticality Experiments Research Center. A total of ten preliminary critical experiments were designed and optimized for Zr and ZrHx nuclear data sensitivities using the MCNP-Particle Swarm Optimization methodology in the thermal, epithermal, intermediate, and fast neutron energy regions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2026

Hydrodynamic Analysis and Optimization of Aquantis Marine Turbine: Cooperative Research and Development (Final Report)

The primary aim of this proposal is to improve the accurate prediction of hydrodynamic performance and dynamic load responses of the AQ10 floating axial-flow tidal turbine with a tri-cat mooring configuration. The validation of reduced-order modeling approaches with high-fidelity model will be implemented. Additionally, the frequency response domain, Response Amplitude Floating Wind (RAFT) toolbox plus an optimizer expanded for marine hydrokinetic turbines under the Submarine Hydrokinetic And Riverine Kilo-megawatt. Systems (SHARKS) program will be used for designing and exploring different key design parameters (platform dimension, mooring layout and its parameters) of next marine hydrokinetic (MHK) turbine generation.

16 TIDAL AND WAVE POWER↗

DOE OSTI2023

A Schottky Tune Meter for the Fermilab Mu2E Delivery Ring

The Mu2E experiment will measure the ratio of the rate of the neutrinoless, coherent conversion of muons into electrons as a measure of Charged Lepton Flavor Violation. As part of the Mu2E experiment, a proton storage ring, called the Delivery Ring, will utilize resonant extraction to slow-spill protons to the experiment. To regulate and optimize the Delivery Ring resonant extraction process, a fast tune measurement scheme will be required. This Mu2E tune meter will measure the average tune and the tune spectrum, in multiple time slices, through the entire resonant extraction cycle of nominally 43 msec. The Mu2E tune meter system utilizes vertical and horizontal 21.4 MHz Schottky detector resonant pickups, taken from the decommissioned Tevatron, high-gain amplifiers and digital down-conversion FPGA logic for its signal processing. This paper will present the design of this Schottky tune meter as well as tune measurements from the Mu2E delivery ring.

43 PARTICLE ACCELERATORS↗

DOE OSTI2023

Multi-layered Energy Management Framework for Extreme Fast Charging Stations Considering Demand Charges, Battery Degradation, and Forecast Uncertainties

To achieve a cost-effective and expeditious charging experience for extreme fast charging station (XFCS) owners and electric vehicle (EV) users, the optimal operation of XFCS is crucial. It is however challenging to simultaneously manage the profit from energy arbitrage, the cost of demand charges, and the degradation of a battery energy storage system (BESS) under uncertainties. This paper, therefore, proposes a multi-layered multi-time scale energy flow management framework for an XFCS by considering long- and short-term forecast uncertainties, monthly demand charges reduction, and BESS life degradation. In the proposed approach, an upper scheduling layer (USL) ensures the overall operation economy and yields optimal scheduling of the energy resources on a rolling horizon basis, thereby considering the long-term forecast errors. A lower dispatch layer (LDL) takes the short-term forecast errors into account during the real-time operation of the XFCS. Per the latest research, monthly demand charges can be as high as 90% of the total monthly bills for EV fast charging stations; to this end, this paper takes the first attempt at the reduction of demand charges cost by considering the trade-off between the energy cost and monthly demand charges. Contrasting literature, this work allocates an energy reserve in the BESS stored energy to deal with the impact of short-term forecast errors on the optimized real-time operation of the XFCS. Moreover, degradation modeling considers the trade-off between short-term benefits and long-term BESS life degradation. As a result, case studies and a comparative analysis prove the efficacy of the proposed framework.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Series FACTS Devices for Increasing Resiliency in Severe Weather Conditions

Severe weather conditions are low-probability, high-impact events that affect grid operations. The majority of power outages are caused by severe weather conditions. Grid resiliency to weather events can be enhanced by decreasing the reliance on its affected sections. One way to do this is to reduce the power flow through lines vulnerable to severe weather. If a line is disconnected, its initial power flow is distributed through the neighbor lines, which may cause congestion in the grid. FACTS devices can be used to control the power flow of lines that have a higher chance of power outages. Most previous works do not consider weather events in power flow control. In this work, a linearized optimal power flow (OPF)–based algorithm is developed to minimize the real power flow of vulnerable lines considering the thermal limits of lines to prevent infeasible solutions; the simulation is fast, making it suitable for large-scale systems. The proposed optimization problem is presented as a mixed-integer linear program (MILP), making it capable of using short-term load forecasting due to its high solution speed. The proposed optimization problem considers multiple lines with different outage probabilities and the uncertainties of the weather forecast. Moreover, it estimates the power reduction in vulnerable lines due to changes in the series FACTS devices. The performance of the proposed optimization problem is tested on IEEE 14-, 30-, and 118-bus systems for several scenarios. The results are validated with the AC power flow results from MATPOWER.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Sparse Cholesky factorization for solving nonlinear PDEs via Gaussian processes

In recent years, there has been widespread adoption of machine learning-based approaches to automate the solving of partial differential equations (PDEs). Among these approaches, Gaussian processes (GPs) and kernel methods have garnered considerable interest due to their flexibility, robust theoretical guarantees, and close ties to traditional methods. They can transform the solving of general nonlinear PDEs into solving quadratic optimization problems with nonlinear, PDE-induced constraints. However, the complexity bottleneck lies in computing with dense kernel matrices obtained from pointwise evaluations of the covariance kernel, and its partial derivatives, a result of the PDE constraint and for which fast algorithms are scarce. The primary goal of this paper is to provide a near-linear complexity algorithm for working with such kernel matrices. We present a sparse Cholesky factorization algorithm for these matrices based on the near-sparsity of the Cholesky factor under a novel ordering of pointwise and derivative measurements. The near-sparsity is rigorously justified by directly connecting the factor to GP regression and exponential decay of basis functions in numerical homogenization. We then employ the Vecchia approximation of GPs, which is optimal in the Kullback-Leibler divergence, to compute the approximate factor. This enables us to compute ϵ-approximate inverse Cholesky factors of the kernel matrices with complexity O(N log d (N/ϵ)) in space and O(N log 2d (N/ϵ)) in time. We integrate sparse Cholesky factorizations into optimization algorithms to obtain fast solvers of the nonlinear PDE. We numerically illustrate our algorithm’s near-linear space/time complexity for a broad class of nonlinear PDEs such as the nonlinear elliptic, Burgers, and Monge-Ampère equations. In summary, we provide a fast, scalable, and accurate method for solving general PDEs with GPs and kernel methods.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Fast Fourier transform evaluation of the Fresnel integral for gravitational-wave lensing

Gravitational waves (GWs) exhibit wave-optics effects when their wavelength is comparable to the scale of the gravitational lens. This may occur in lensing from galactic subhalos in GWs emitted by binary black-hole mergers and is gaining interest as a novel probe of dark matter. Predictions for observables in these cases ultimately rely on evaluating a Fresnel integral that quantifies the effect of lensing on the amplitude of a GW at a given frequency. However, numerical evaluation of this Fresnel integral is tricky, and several algorithms and publicly available codes that implement it have been developed. Here, we show that the dependence of this integral on the lens position can be written as a two-dimensional Fourier transform. Modern FFT techniques then enable rapid evaluation at all-sky positions simultaneously for general lenses without symmetry. Vectorization of FFT routines allows for derivatives with respect to model parameters to be obtained with only incremental additional computational cost. If the lens is axisymmetric, further speedups can be achieved with recently developed techniques for nonuniform fast Hankel transforms. To demonstrate, we make available Fresnel Integral Optimization with Nonuniform Transforms (fiona), an efficient and accurate code that is significantly faster than current methods for dense source grids, reaching 2 orders of magnitude speedups for ∼10 6 GW-emitting points. As part of FIONA , we developed code that provides vectorized nonuniform fast Hankel transforms that may have other uses (e.g., calculation of cosmological two-point correlation functions) beyond those considered here.

dark matter↗

DOE OSTI2022

Adaptive Space-Time Methods for Large Scale Optimal Design

When modeling complex physical systems with advanced dynamics, such as shocks and singularities, many classic methods for solving partial differential equations can return inaccurate or unusable results. One way to resolve these complex dynamics is through r-adaptive refinement methods, in which a fixed number of mesh points are shifted to areas of high interest. The mesh refinement map can be found through the solution of the Monge-Ampére equation, a highly nonlinear partial differential equation. Due to its nonlinearity, the numerical solution of the Monge-Ampére equation is nontrivial and has previously required computationally expensive methods. In this report, we detail our novel optimization-based, multigrid-enabled solver for a low-order finite element approximation of the Monge-Ampére equation. This fast and scalable solver makes r-adaptive meshing more readily available for problems related to large-scale optimal design. Beyond mesh adaptivity, our report discusses additional applications where our fast solver for the Monge-Ampére equation could be easily applied.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2026

An overview of 3D field optimization for control of transport and edge instabilities on KSTAR

An international team from several laboratories and universities has made key advances over the last few years in the control of plasma transport and edge instabilities with applied 3D fields in the KSTAR tokamak to optimize long pulse operation scenarios. This overview begins with the optimization of both core and edge resonant magnetic perturbations (RMP) to improve fast ion confinement to avoid excessive limiter heat loads due to fast ion losses and successful modeling of the experimental results. Integrated and advanced plasma control techniques with machine learning (ML) and adaptive control were then used to optimize the 3D field spectrum in real-time to control edge localized modes (ELMs) while avoiding core locked modes that could disrupt the plasma. Accelerating the offline model of 3D fields with a surrogate ML model can optimize ELM suppression in the edge while limiting the impact of the applied RMP fields deeper in the plasma core in real-time. In addition, the impact of the 3D fields on the divertor heat load has been modeled and compared with experimental measurements. An analysis of a multi-machine database including KSTAR has been performed to better understand the metrics for the observed RMP thresholds for ELM suppression and the resulting plasma performance. Predictive modeling of the operational space for ELM suppression and density pumpout due to RMP has shown the importance of magnetic islands in the plasma edge and their impact on plasma turbulence. This research has culminated in the development of successful long pulse operational scenarios on KSTAR while attempting to overcome challenges of the new tungsten divertor.

3D fields↗

DOE OSTI2021

Advanced battery modeling for interfacial phenomena and optimal charging

Lithium ion batteries are one of the most promising energy storage systems for portable devices, transportation, and renewable grids. To meet the increasing requirements of these applications, higher energy density and areal capacity, long cycle life, fast charging rate and enhanced safety for lithium ion battery (LIBs) are urgently needed. To solve these challenges, the relevant physics at different length scale need to be understood. However, experimental study is time consuming and limited in small scale’s study. Modeling techniques provide us powerful tools to get a deep understanding of the relevant physics and find optimal solutions. This work focuses on studying the mechanism in advanced battery engineering techniques and developing a new charging algorithm by model-based optimization. The research topics are divided into six topics and each topic is reported as a form of journal publication. Paper Ⅰ provides a new aspect of how ALD coating improves the lithium ion diffusion at electrode particles. Paper Ⅱ explains the mechanisms by which 3D electrodes enhance battery performance and reveals guidelines for optimized 3D electrode designs by a 3D electrochemical-mechanical battery model. Paper Ⅲ investigates the electrolyte concentration impact on SEI layer growth and Li plating, especially under high charge rates. Paper Ⅳ proposes an optimized charging protocol for fast charging for reducing the charging time with minimal degradation. Paper Ⅴ reports a comprehensive degradation model for degradation estimation and life predication of energy storage system (ESS). Paper Ⅵ is a study of temperature-dependent state of charge (SOC) estimation for battery pack.

25 ENERGY STORAGE↗

DOE OSTI2025

The scoping, design, and plasma physics optimization of the Eos neutron source stellarator

On the path to a fusion pilot plant, Thea Energy plans to build Eos, a sub-breakeven, deuterium-deuterium, beam-target fusion, stellarator neutron source facility for producing tritium and other valuable radioisotopes. In this paper, a set of 1D plasma physics models are coupled and used to design the operating point of the facility and predict performance. At this foundational stage of the design, analytic and approximate models are sufficient to capture the leading-order effects, and fast enough to run in the inner loop of an optimizer. Higher-fidelity analyses will follow. Models of 1D profile-dependent neutral beam stopping, ion beam slowing down, beam-target fusion, electron-ion classical heat transfer, energy confinement (ISS04), beam pressure, beam heating of ions and electrons, beam-beam fusion fraction, and neutral beam injection and gyrotron heating electrical efficiencies are included. A numerical optimizer is used to determine the minimum required facility electric power to generate tritium at a given rate. A potentially advantageous regime is described in which modern precisely-quasisymmetric stellarators, new high-temperature superconductors, ITER-derived neutral beam injection, and new high-frequency gyrotrons enable a suitible target plasma with hot electrons, cold ions, peaked density and temperature profiles, and high beam-injected ion density. It appears possible at this time for a facility with a medium-scale and medium-strength stellarator whose required facility electric power is less than 40 MW to produce $2.5\times 10^{17}$ neutrons s -1 for the production of radioisotopes. With the addition of a tritium breeding blanket, such a facility could produce 0.2 grams d -1 or 70 grams yr -1 of tritium.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Innovative Nuclear Materials Outboard-A Project Specimen Preparation Guide

The Innovative Nuclear Materials (INM) Program was recently established by the U.S. Department of Energy (DOE) to develop advanced material technologies for use in nuclear reactors. The INM program is presently focused on researching in-core non-fueled materials for application in fast spectrum nuclear reactors. The widespread deployment of fast reactors continues to be a prominent aspiration for advanced nuclear technology developers. However, companies working to license these reactors have no choice but to rely on historic material technologies since further optimization and advancement of these materials is impeded by the lack of fast neutron irradiation test facilities. INM-OA is a non-fueled drop-in experiment which will irradiate material specimens of interest to fast reactor applications. This experiment will be irradiated at Idaho National Laboratory (INL) in the Advanced Test Reactor (ATR) outboard-A (OA) position during normal and high temperature steady state (HTSS) cycles. It will include material specimens supplied by members of the INM program and will utilize a cadmium-lined basket to filter out incident thermal neutrons, thus simulating a faster neutron energy spectrum. Material specimens will undergo post-irradiation examination including microscopy and mechanical testing. In addition to absorption reactions, fast neutrons cause microstructural damage in materials by atom displacement, which can cause exacerbated changes in physical properties and behavior. Thus, the data obtained from the INM-OA experiment will be crucial for understanding the engineering-scale behavior of reactor materials. This document is intended for the Principal Investigators providing samples for this project. Topics included are a general description of the experiment, the irradiation experiment/capsule design, sample geometries, number of samples to be provided, documentation to be provided, a brief list potentially useful characterization methods that can be leveraged at INL, and other miscellaneous requirements specific to this project. This document is intended for informational use only.

innovative nuclear materials↗

DOE OSTI2023

Development of high-performance long-pulse discharge in KSTAR

High-performance long-pulse plasma operation is essential for producing economically viable fusion energy in tokamak devices. To achieve such discharges in KSTAR, firstly, the rapid increase in the temperature of plasma-facing components was mitigated. The temperature increase of the poloidal limiter, especially, was associated with beam-driven fast ion orbit loss and the discrepancy of the equilibrium reconstructed with heated magnetic probes of signal drift. The fast ions lost to the poloidal limiter were reduced by optimizing the plasma shape and the composition of neutral beam injection (NBI). This nonlinear signal drift was successfully reduced by a new thermal shielding protector on the magnetic probes. Secondly, a lower loop voltage approach was implemented to reduce a poloidal flux consumption rate. A plasma current of 400 kA and a line-averaged electron density of ~2.0 × 10 19 m –3 were chosen by considering the L–H power threshold, fast ion orbit loss, and beam shine-through power loss for low loop voltage in KSTAR. In addition, the application of electron cyclotron heating also helped maintain the plasma with low loop voltage (~25 mV) by enhancing the NBI-driven current and achieving a high poloidal beta (β P ) state. KSTAR has achieved a long pulse (~90 s) operation with the high performance of β P $\leqslant$ 2.7, thermal energy confinement enhancement factor (H 98y2 ) ~ 1.1, and fraction of non-inductive current (f NI ) $\leqslant$ 0.96. Still, gradual degradation of the plasma performance has been observed over time in the discharges. In one of the long-pulse discharges, β P reduced by ~18% over the time of ~8τ R (current relaxation time, τ R ~5 s) and ~1067τ E,th (thermal energy confinement time, τ E,th ~45 ms). The degradation may be closely associated with weak, yet growing, and persistent toroidal Alfvén eigenmodes and their effect on fast ion confinement.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

A fast reduced model for a shell-and-tube based latent heat thermal energy storage heat exchanger and its application for cost optimal design by nonlinear programming

Numerical simulation of latent heat thermal energy storage (LHTES) systems plays a fundamental role in studying the physical process and guiding the engineering design. Discretization of the PDEs describing the nonlinear solidification/melting process of phase change materials (PCMs) leads to a large-scale complex dynamics system, where the system behavior depends on a set of parameters. In a design setting, repeated model evaluations are required over the set of parameters results in significant computational burden. In this paper, an explicit analytic solution was built for the propagation of the solidification front in a cylindrical coordinate. The analytic solution approach is further employed to develop a low computational reduced model (RM) as a module for a shell-and-tube based LHTES heat exchanger. The levelized Cost of Energy (LCOE) is used as a design metric and the RM model is used to apply system-level constraints in the nonlinear programming formulation that facilitates efficient global optimal design of the PCM properties, flow conditions and tube geometries. The use of LCOE as the design metric prevents over design of the heat transfer rate and also establishes a fair ground for evaluation of different thermal storage technologies and their integrated applications with other systems. Optimal results showed that a higher effectiveness results in a higher LCOE; the velocity of the HTF and the length of the channel are highly correlated with each other; both larger PCM latent energy and conductivity result in lower LCOE.

25 ENERGY STORAGE↗

DOE OSTI2021

Charged particle tracking with quantum annealing optimization

Abstract At the High Luminosity Large Hadron Collider (HL-LHC), traditional track reconstruction techniques that are critical for physics analysis will need to be upgraded to scale with track density. Quantum annealing has shown promise in its ability to solve combinatorial optimization problems amidst an ongoing effort to establish evidence of a quantum speedup. As a step towards exploiting such potential speedup, we investigate a track reconstruction approach by adapting the existing geometric Denby-Peterson (Hopfield) network method to the quantum annealing framework for HL-LHC conditions. We develop additional techniques to embed the problem onto existing and near-term quantum annealing hardware. Results using simulated annealing and quantum annealing with the D-Wave 2X system on the TrackML open dataset are presented, demonstrating the successful application of a quantum annealing algorithm to the track reconstruction challenge. We find that combinatorial optimization problems can effectively reconstruct tracks, suggesting possible applications for fast hardware-specific implementations at the HL-LHC while leaving open the possibility of a quantum speedup for tracking.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Anisotropic Thermally Conductive Composites Enabled by Acoustophoresis and Stereolithography

Opportunities to improve thermal management in electronic devices are currently hindered by processing constraints that limit thermal conductivity in polymer-matrix composites. Active patterning of filler particles is a promising route to improve conductivity while retaining processability by improving particle contact density and directing heat along optimized pathways. Here, we employ acoustic patterning to align and compact filler particles into stripes during stereolithographic 3D printing. This approach produces polymer-based composite materials with highly efficient embedded heat transport pathways which reach 95 vol% particle utilization (relative to the parallel conduction upper limit). These composites exhibit anisotropic thermal conductivity up to 300% higher than unpatterned composites, with in-plane anisotropy ratios of up to 350%. Combining this high conductivity with 3D printing enables materials with engineered heat networks that optimize transport from hot spots to heatsinks while maintaining low viscosity for fast particle patterning and for infiltration around electronic components. Finally, numerical simulations of acoustic assembly of particles with varied geometry, when compared to experimentally characterized particle packing, illuminate pathways for further improving conductivity by optimizing particle geometry for alignment and stacking of particles with maximum contact surface area.

36 MATERIALS SCIENCE↗

DOE OSTI2022

A room-temperature polarization-sensitive CMOS terahertz camera based on quantum-dot-enhanced terahertz-to-visible photon upconversion

Detection of terahertz (THz) radiation has many potential applications, but presently available detectors are limited in many aspects of their performance, including sensitivity, speed, bandwidth and operating temperature. Most do not allow the characterization of THz polarization states. Recent observation of THz-driven luminescence in quantum dots offers a possible detection mechanism via field-driven interdot charge transfer. Here, we demonstrate a room-temperature complementary metal–oxide–semiconductor THz camera and polarimeter based on quantum-dot-enhanced THz-to-visible upconversion mechanism with optimized luminophore geometries and fabrication designs. Besides broadband and fast responses, the nanoslit-based sensor can detect THz pulses with peak fields as low as 10 kV cm–1. A related coaxial nanoaperture-type device shows a to-date-unexplored capability to simultaneously record the THz polarization state and field strength with similar sensitivity.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2023

Absolute electron density fluctuation reconstruction for two-dimensional hydrogen beam emission spectroscopy

Scrape-off layer (SOL) and edge plasma turbulence significantly contribute to the radial particle and heat transport, lowering the plasma confinement and increasing the heat load on the plasma facing components. SOL turbulence is predominantly intermittent, which manifests in the occurrence of isolated density filaments or blobs. Filaments propagate radially outward toward plasma facing components, limiting their lifetime by erosion and sputtering. To characterize this phenomenon in detail, few diagnostic techniques are available. Beam emission spectroscopy is a diagnostic capable of measuring plasma turbulence in both SOL and edge plasmas. Due to the finite lifetime of the excitation states during the beam–plasma interaction and the misalignment between the optics and the magnetic field, spatial smearing is introduced in the measurement. In this paper, a novel method is introduced to overcome this hindering effect by inverting the fluctuation response matrix on an optimally smoothed signal. We show that this method is fast and provides significantly more accurate absolute density fluctuation reconstruction than the direct inversion technique. Here, the presented method is usable for all types of beam emission diagnostics where the spatial resolution is higher than the combined smearing of the atomic physics and the observation.

47 OTHER INSTRUMENTATION↗