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At least 595 records · Page 33

Fusion Materials Science and Technology Research Needs: Now and During the ITER era

The plasma facing components, first wall and blanket systems of future tokamak-based fusion power plants arguably represent the single greatest materials engineering challenge of all time. Indeed, the United States National Academy of Engineering has recently ranked the quest for fusion as one of the top grand challenges for engineering in the 21st Century. These challenges are even more pronounced by the lack of experimental testing facilities that replicate the extreme operating environment involving simultaneous high heat and particle fluxes, large time varying stresses, corrosive chemical environments, and large fluxes of 14-MeV peaked fusion neutrons. This paper will review, and attempt to prioritize, the materials research and development challenges facing fusion nuclear science and technology into the ITER era and beyond to DEMO. In particular, the presentation will highlight the materials degradation mechanisms we anticipate to occur in the fusion environment, the temperature- displacement goals for fusion materials and plasma facing components and the near and long-term materials challenges required for both ITER, a fusion nuclear science facility and longer term ultimately DEMO.

Wirth, Brian D.↗

Pellet Injection Technology and Its Applications on ITER

Cryogenic pellet injectors for use in fusion research have been under development at Oak Ridge National Laboratory for over 30 years. The original application of the technology was to add fuel to magnetically confined plasmas to replace D-T ions that are consumed in the fusion reactions or lost due to transport out of the confining magnetic fields. This application is still the primary use for pellet injection and is planned for implementation on the ITER burning plasma experiment. More recently, there have been additional applications for the injection of cryogenic pellets in the areas of disruption and edge-localized mode mitigation. Injectors for these applications are also being implemented for ITER, which require refinements of the technology for production and shattering of very large pellets and production of very small high repetition rate pellets, respectively. Details of these applications and injection system designs are presented.

Baylor, Larry R.↗

Distribution System State Estimation Using a Multiple Iteration Extended Kalman Filter Approach

To support the operation of modern distribution systems, operators require real-time visibility into system states. Due to a lack of measurements and unbalanced operation, the state estimation in distribution systems is challenging as compared to transmission systems. This paper proposes the utilization of a Multiple Iteration - Extended Kalman Filter based approach for the distribution system state estimation. This modified version of the baseline extended Kalman filter iterates over the update step multiple times thereby reducing the estimation error. The proposed algorithm along with the auxiliary algorithms such as bad data detection is integrated into a co-simulation environment. Case studies show that the proposed state estimation method can result in a lesser estimation error as compared to the baseline approach.

Bhatti, Bilal Ahmad↗

Signal-Preserving Erratic Noise Attenuation via Iterative Robust Sparsity-Promoting Filter

Sparse domain thresholding filters operating in a sparse domain are highly effective in removing Gaussian random noise under Gaussian distribution assumption. Erratic noise, which designates non-Gaussian noise that consists of large isolated events with known or unknown distribution, also needs to be explicitly taken into account. However, conventional sparse domain thresholding filters based on the least-squares (LS) criterion are severely sensitive to data with high-amplitude and non-Gaussian noise, i.e., the erratic noise, which makes the suppression of this type of noise extremely challenging. Here, in this paper, we present a robust sparsity-promoting denoising model, in which the LS criterion is replaced by the Huber criterion to weaken the effects of erratic noise. The random and erratic noise is distinguished by using a data-adaptive parameter in the presented method, where random noise is described by mean square, while the erratic noise is downweighted through a damped weight. Different from conventional sparse domain thresholding filters, definition of the misfit between noisy data and recovered signal via the Huber criterion results in a nonlinear optimization problem. With the help of theoretical pseudoseismic data, an iterative robust sparsity-promoting filter is proposed to transform the nonlinear optimization problem into a linear LS problem through an iterative procedure. The main advantage of this transformation is that the nonlinear denoising filter can be solved by conventional LS solvers. Lastly, tests with several data sets demonstrate that the proposed denoising filter can successfully attenuate the erratic noise without damaging useful signal when compared with conventional denoising approaches based on the LS criterion.

97 MATHEMATICS AND COMPUTING↗

Gradient Coding With Iterative Block Leverage Score Sampling

Gradient coding is a method for mitigating straggling servers in a centralized computing network that uses erasure-coding techniques to distributively carry out first-order optimization methods. Randomized numerical linear algebra uses randomization to develop improved algorithms for large-scale linear algebra computations. In this study, we propose a method for distributed optimization that combines gradient coding and randomized numerical linear algebra. The proposed method uses a randomized ℓ 2 -subspace embedding and a gradient coding technique to distribute blocks of data to the computational nodes of a centralized network, and at each iteration the central server only requires a small number of computations to obtain the steepest descent update. The novelty of our approach is that the data is replicated according to importance scores, called block leverage scores, in contrast to most gradient coding approaches that uniformly replicate the data blocks. Furthermore, we do not require a decoding step at each iteration, avoiding a bottleneck in previous gradient coding schemes. We show that our approach results in a valid ℓ 2 -subspace embedding, and that our resulting approximation converges to the optimal solution.

97 MATHEMATICS AND COMPUTING↗

Modifications to the JET Shattered Pellet Injector to Optimize Disruption Mitigation Experiments for Supporting ITER’s DMS Design

Shattered pellet injection (SPI) experiments on Joint European Torus (JET) are an important element in determining the physics basis for mitigating disruptions in ITER. Here, the initial design of the JET SPI system included three barrels to produce pellets with diameters of 4.5, 8.1, and 12.5 mm. The variability of the pellet speed by operating with and without a mechanical punch was limited and led to poor pellet integrity, so the mechanical punch was removed. Fragment size distribution is a function of pellet speed and the desire to change the resulting fragment size distribution was not originally a requirement. After the first set of SPI experiments on JET, different pellet sizes were considered to enable dual injection experiments with identical pellet diameters. It was also determined that speed control is necessary to improve experimental repeatability and to determine how the fragment size distribution impacts mitigation performance. Two barrels were fabricated to form pellets of 10 mm diameter and a third to form an 8.1 mm diameter pellet. New propellant valves were also fabricated and characterized to improve repeatability and overall performance. To have fine control of pellet speed, inserts to reduce the breech volume were fabricated and installed. Laboratory testing was conducted to ensure pellet release and provide a comparison of propellant gas delivered versus pellet speeds for a range of pellet types and mixtures. This article will also discuss how lessons learned from the JET SPI modifications can be applied to other SPI systems, such as the ITER SPI system, as controlling pellet release with the least amount of propellant gas is essential for optimal SPI effectiveness.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

An Iterative Response-Surface-Based Approach for Chance-Constrained AC Optimal Power Flow Considering Dependent Uncertainty

A modern power system is characterized by a stochastic variation of the loads and an increasing penetration of renewable energy generation, which results in large uncertainties in its states. These uncertainties bring formidable challenges to the power system planning and operation process. To address these challenges, we propose a cost-effective, iterative response-surface-based approach for the chance-constrained AC optimal power-flow problem that aims to ensure the secure operation of the power systems considering dependent uncertainties. Starting from a stochastic-sampling-based framework, we first utilize the copula theory to simulate the dependence among multivariate uncertain inputs. Then, to reduce the prohibitive computational time required in the traditional Monte-Carlo method, we propose, instead of using the original complicated power-system model, to rely on a polynomial-chaos-based response surface. This response surface allows us to efficiently evaluate the time-consuming power-system model at arbitrary distributed sampled values with a negligible computational cost. This further enables us to efficiently conduct an online stochastic testing for the system states that not only screens out the statistical active constraints, but also assists in a better design of the tightened bounds without using any Gaussian or symmetric assumption. Finally, an iterative procedure is executed to fine-tune the optimal solution that better satisfies a predefined probability. The simulations conducted in multiple test systems demonstrate the excellent performance of the proposed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Iterative Stress Reconstruction Algorithm to Estimate Three-Dimensional Residual Stress Fields in Manufactured Components

Residual stress (RS) significantly impacts the mechanical performance of components. Measurement of RS often provides incomplete data in terms of components of stress and spatial density. Employing such fields in finite element simulations results in significant modification of the field to achieve equilibrium and compatibility among strains. To overcome this, an iterative stress reconstruction algorithm (ISRA) is developed to estimate 3D RS fields that satisfy equilibrium, are stress component-wise complete, and represent the characterized data sampled. An Al 7075-T651 plate and an additively manufactured (AM) A36 steel wall are considered for RS reconstruction using measurement data from the literature. A maximum variation of ~2.5 MPa in the Al plate, and ~10 MPa in the steel wall are observed between the reconstructed and measured stresses. Furthermore, unknown stress components emerge and reach significant magnitudes (upto ~2.3 MPa in the Al plate and ~45 MPa in the AM wall) during ISRA. Indeed, it is found that minor errors in measurement or data processing are eliminated through the physical requirements during ISRA. Employing a reconstructed RS field is hence not just more accurate given its compatibility, but it additionally corrects for minor errors in measurement. Furthermore, it is found that spatially dense measurement data result in convergence with fewer iterations. Finally, although ISRA yields a nonunique solution dependent on boundary conditions, measurement errors, fitting errors, and mesh density, it accommodates for uncertainties and inaccuracies in measurement, as opposed to failing to reach a physically realistic converged solution.

42 ENGINEERING↗

Iterative multi-task learning and inference from seismic images

Seismic interpretation aims to extract quantitative and interpretable attributes from a seismic image produced using some migration method to inform characteristics of a subsurface reservoir or target of interest. Current paradigms for computing seismic attributes mostly rely on single-task algorithms. We develop an iterative, multi-task machine learning method to learn and infer multiple attributes from a seismic image. This method is composed of two stages: a multi-task inference stage and a multi-modal, multi-task refinement stage. The basic mechanism of this method is that we train a multi-task inference neural network (NN) to estimate a set of attributes, including a relative geological time (RGT), a denoised higher-resolution (DHR) seismic image, and multiple fault attributes (including probability, dip, and strike), from a low-resolution, noisy seismic image; then we input the inferred attributes to a multi-task refinement NN to enhance the raw inference results iteratively. The two multi-task NNs are trained separately based on synthetic seismic images and associated attributes generated by a geological modeling algorithm. The software we intend to release is a PyTorch implementation of this multi-task learning method for both 2D and 3D cases along with scripts to run the training/validation. The algorithm and software can be a useful tool for automatic seismic interpretation.

Gao, Kai↗

ARCS: Agentic Retrieval-Augmented Code Synthesis with Iterative Refinement

Agentic Retrieval-Augmented Code Synthesis with Iterative RefinementIn supercomputing, efficient and optimized code generation is essential to leverage high-performance systems effectively. We have developed Agentic Retrieval-Augmented Code Synthesis (ARCS), an advanced framework for accurate, robust, and efficient code generation, completion, and translation. ARCS integrates Retrieval-Augmented Generation (RAG) with Chain-of-Thought (CoT) reasoning to systematically break down and iteratively refine complex programming tasks. An agent-based RAG mechanism retrieves relevant code snippets, while real-time execution feedback drives the synthesis of candidate solutions. This process is formalized as a state-action search tree optimization, balancing code correctness with editing efficiency. Evaluations on the Geeks4Geeks and HumanEval benchmarks demonstrate that ARCS significantly outperforms traditional prompting methods in translation and generation quality. By enabling scalable and precise code synthesis, ARCS offers transformative potential for automating and optimizing code development in supercomputing applications, enhancing computational resource utilization

Bhattarai, Manish [Los Alamos National Labs]↗

Disruption Mitigation System Developments and Design for ITER

A disruption mitigation system (DMS) is under design for ITER to inject sufficient material deeply into the plasma for rapid plasma thermal shutdown and collisional suppression of any resulting runaway electrons. Progress on the development and design of both a shattered pellet injector (SPI) that produces large solid cryogenic pellets to provide reliable deep penetration of material and a fast opening high flow rate gas valve for massive gas injection (MGI) is presented. Cryogenic pellets of deuterium and neon up to 25 mm in size have been formed and accelerated with a prototype injector and a full scale prototype MGI valve is now in testing. Implications of the design with respect to response time and reliability at the proposed injector locations on ITER are discussed.

Baylor, Larry↗

Multimachine data–based prediction of high-frequency sensor signal noise for resistive wall mode control in ITER

The high-frequency noise measured by magnetic sensors, at levels above the typical frequency of resistive wall modes, is analyzed across a range of present tokamak devices including DIII-D, JET, MAST, ASDEX Upgrade, JT-60U, and NSTX. A high-pass filter enables identification of the noise component with Gaussian-like statistics that shares certain common characteristics in all devices considered. A conservative prediction is made for ITER plasma operation of the high-frequency noise component of the sensor signals, to be used for resistive wall mode feedback stabilization, based on the multimachine database. The predicted root-mean-square n = 1 (n is the toroidal mode number) noise level is 10 4 to 10 5 G/s for the voltage signal, and 0.1 to 1 G for the perturbed magnetic field signal. The lower cutoff frequency of the Gaussian pickup noise scales linearly with the sampling frequency, with a scaling coefficient of about 0.1. As a result, these basic noise characteristics should be useful for the modeling-based design of the feedback control system for the resistive wall mode in ITER.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Alcator C-Mod Experiments in Support of the ITER Baseline 15 MA Scenario

Experiments on Alcator C-Mod have addressed several issues for the ITER 15 MA baseline scenario from 2009-2012. Rampup studies show ICRF can save significant V-s, and that an H-mode in the ramp can be utilized to save 50% more. ICRF modifications to li(1) are minimal, although the Te profile is peaked relative to ohmic in the plasma center, and alter sawtooth onset times. Rampdown studies show H-modes can be routinely sustained, avoiding an OH coil over-current associated with the H-L transition, that fast rampdowns are preferred, the density drops with Ip, and that the H-L transition occurs at P loss /P thr,LH ~ 1.0-1.3 at n/n Gr ~ 0.85. Flattop plasmas targeting ITER baseline parameters have been sustained for 20 τ E or 8-13 τ CR , but only reach H 98 ~ 0.6 at n/n Gr = 0.85, rising to 0.9 at n/n Gr = 0.65.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

STELLOPT Modeling of the 3D Diagnostic Response in ITER

The ITER three dimensional diagnostic response to an n=3 resonant magnetic perturbation is modeled using the STELLOPT code. The in-vessel coils apply a resonant magnetic perturbation (RMP) fi eld which generates a 4 cm edge displacement from axisymmetry as modeled by the VMEC 3D equilibrium code. Forward modeling of flux loop and magnetic probe response with the DIAGNO code indicates up to 20 % changes in measured plasma signals. Simulated LIDAR measurements of electron temperature indicate 2 cm shifts on the low field side of the plasma. This suggests that the ITER diagnostic will be able to diagnose the 3D structure of the equilibria.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

An Easy Method To Accelerate An Iterative Algebraic Equation Solver

This article proposes to add a simple term to an iterative algebraic equation solver with an order n convergence rate, and to raise the order of convergence to (2n - 1). In particular, a simple algebraic equation solver with the 5th order convergence but uses only 4 function values in each iteration, is described in details. When this scheme is applied to a Newton-Raphson method of the quadratic convergence for a system of algebraic equations, a cubic convergence can be achieved with an low overhead cost of function evaluation that can be ignored as the size of the system increases.

97 MATHEMATICS AND COMPUTING↗

SciDAC Center for Simulation of Wave-Plasma Interactions - Iterated Finite-Orbit Monte Carlo Simulations with Full-Wave Fields for Modeling Tokamak ICRF Wave Heating Experiments - Final Report

This final report describes the work performed under U.S. Department of Energy Cooperative Agreement DE-FC02-08ER54954 for the period April 1, 2011 through March 31, 2013. The goal of this project was to perform iterated finite-orbit Monte Carlo simulations with full-wall fields for modeling tokamak ICRF wave heating experiments. In year 1, the finite-orbit Monte-Carlo code ORBIT-RF and its iteration algorithms with the full-wave code AORSA were improved to enable systematical study of the factors responsible for the discrepancy in the simulated and the measured fast-ion FIDA signals in the DIII-D and NSTX ICRF fast-wave (FW) experiments. In year 2, ORBIT-RF was coupled to the TORIC full-wave code for a comparative study of ORBIT-RF/TORIC and ORBIT-RF/AORSA results in FW experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

US NDC Modernization Iteration E2 Prototyping Report: User Interface Framework

During the second iteration of the US NDC Modernization Elaboration phase (E2), the SNL US NDC Modernization project team completed follow-on Rich Client Platform (RCP) exploratory prototyping related to the User Interface Framework (UIF). The team also developed a survey of browser-based User Interface solutions and completed exploratory prototyping for selected solutions. This report presents the results of the browser-based UI survey, summarizes the E2 browser-based UI and RCP prototyping work, and outlines a path forward for the third iteration of the Elaboration phase (E3).

97 MATHEMATICS AND COMPUTING↗