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At least 667 records · Page 37

Disruption event characterization and forecasting in tokamaks

Disruption prediction and avoidance is a critical need for next-step tokamaks, such as ITER. Disruption Event Characterization and Forecasting (DECAF) research fully automates analysis of tokamak data to determine chains of events that lead to disruptions and to forecast their evolution allowing sufficient time for mitigation or complete avoidance of the disruption. Disruption event chains related to local rotating or global magnetohydrodynamic (MHD) modes and vertical instability are examined with warnings issued for many off-normal physics events, including density limits, plasma dynamics, confinement transitions, and profile variations. Along with Greenwald density limit evaluation, a local radiative island power balance theory is evaluated and compared to the observation of island growth. Automated decomposition and analysis of rotating tearing modes produce physical event chains leading to disruptions. A total MHD state warning model comprised of 15 separate criteria produces a disruption forecast about 180 ms before a standard locked mode detector warning. Single DECAF event analyses have begun on KSTAR, MAST, and NSTX/-U databases with thousands of shot seconds of device operation using from 0.5 to 1 × 10 6 tested sample times per device. An initial multi-device database comparison illustrates a highly important result that plasma disruptivity does not need to increase as βN increases. Global MHD instabilities, such as resistive wall modes (RWMs), can give the briefest time period of warning before disruption compared to other physics events. In an NSTX database with unstable RWMs, the mode onset, loss of boundary and current control, and disruption event warnings are found in all cases and vertical displacement events are found in 91% of cases. An initial time-dependent reduced physics model of kinetic RWM stabilization created to forecast the disruption chain predicts instability 84% of the time for experimentally unstable cases with a relatively low false positive rate. Instances of the disruption event chain analysis illustrate dynamics including H–L back transitions for rotating MHD and global RWM triggering events. Furthermore, disruption warnings are issued with sufficient time before the disruption (on transport timescales) to potentially allow active profile control for disruption avoidance, active mode control, or mitigation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Control of power, torque, and instability drive using in-shot variable neutral beam energy in tokamaks

A first-ever demonstration of controlling power and torque injection through time evolution of neutral beam energy has been achieved in recent experiments at the DIII-D tokamak. Pre-programmed waveforms for the neutral beam energy produce power and torque inputs that can be separately and continuously controlled. Previously, these inputs were tailored using on/off modulation of neutral beams resulting in large perturbations (e.g. power swings of over 1 MW). The new method includes, importantly for experiments, the ability to maintain a fixed injected power while varying the torque. In another case, different beam energy waveforms (in the same plasma conditions) produce significant changes in the observed spectrum of beam ion-driven instabilities. Measurements of beam ion loss show that one energy waveform results in the complete avoidance of coherent losses due to Alfvénic instabilities. This new method of neutral beam operation is intended for further application in a variety of DIII-D experiments including those concerned with high-performance steady state scenarios, fast particle effects, and transport in the low torque regime. As a result, developing this capability would provide similar benefits and improved plasma control for other magnetic confinement fusion facilities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

8760-Based Method for Representing Variable Generation Capacity Value in Capacity Expansion Models: Preprint

Capacity expansion models (CEMs) are widely used to evaluate the least-cost portfolio of electricity generators, transmission, and storage needed to reliably serve demand over the evolution of many years or decades. Various CEM formulations are used to evaluate systems ranging in scale from states or utility service territories to national or multi-national systems. CEMs can be computationally complex, and to achieve acceptable solve times, key parameters are often estimated using simplified methods. In this paper, we focus on two of these key parameters associated with the integration of variable generation (VG) resources: capacity value and curtailment. We first discuss common modeling simplifications used in CEMs to estimate capacity value and curtailment, many of which are based on a representative subset of hours that can miss important tail events or which require assumptions about the load and resource distributions that may not match actual distributions. We then present an alternate approach that captures key elements of chronological operation over all hours of the year without the computationally intensive economic dispatch optimization typically employed within more detailed operational models. The updated methodology characterizes the (1) contribution of VG to system capacity during high load and net load hours, (2) the curtailment level of VG, and (3) the potential reductions in curtailments enabled through deployment of storage and more flexible operation of select thermal generators. We apply this alternate methodology to an existing CEM, the Regional Energy Deployment System (ReEDS). Results demonstrate that this alternate approach provides more accurate estimates of capacity value and curtailments by explicitly capturing system interactions across all hours of the year. This approach could be applied more broadly to CEMs at many different scales where hourly resource and load data is available, greatly improving the representation of challenges associate with integration of variable generation resources.

14 SOLAR ENERGY↗

Time evolution of ML-MCTDH wavefunctions. I. Gauge conditions, basis functions, and singularities

We derive a family of equations-of-motion (EOMs) for evolving multi-layer multiconfiguration time-dependent Hartree (ML-MCTDH) wavefunctions that, unlike the standard ML-MCTDH EOMs, never require the evaluation of the inverse of singular matrices. All members of this family of EOMs make use of alternative static gauge conditions than those used for standard ML-MCTDH. These alternative conditions result in an expansion of the wavefunction in terms of a set of potentially arbitrary orthonormal functions, rather than in terms of a set of non-orthonormal and potentially linearly dependent functions, as is the case for standard ML-MCTDH. We show that the EOMs used in the projector splitting integrator (PSI) and the invariant EOM approaches are two special cases of this family obtained from different choices for the dynamic gauge condition, with the invariant EOMs making use of a choice that introduces potentially unbounded operators into the EOMs. As a consequence, all arguments for the existence of parallelizable integration schemes for the invariant EOMs can also be applied to the PSI EOMs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Operando X-ray tomography and sub-second radiography for characterizing transport in polymer electrolyte membrane electrolyzer

Utilizing hydrogen gas as an energy carrier and enabling a hydrogen economy is a promising step towards decarbonization. Water electrolysis is a key process in hydrogen generation, but electrolyzers face a couple technological hurdles before widespread integration could occur. Understanding morphology evolution and transport processes in an operating polymer electrolyte membrane (PEM) electrolyzer is key to reducing cost and increasing efficiency. In this study, combined operando X-ray computed tomography and radiography are used to study transport and degradation in PEM electrolyzers subject to applied current densities. Tomography enables three-dimensional steady-state imaging but does not capture transport subtleties. Radiography is limited to two-dimensions but does capture transient phenomena. The tomography results depict degradation of the catalyst layer on the anode side of the electrolyzer. The rate of degradation was observed to increase as the applied current density increased. The catalyst particle detachment is due to autonomous propulsion during the oxygen evolution reaction. Particles that mechanically rip off the membrane were observed to be redeposited into the porous transport layer. During radiography, sub-second exposure time is required to capture the transient behavior of oxygen evolution, even at the lower current densities (50-200 mAcm -2 ). Various flow regimes were observed in the channel ranging from bubbly to slug flow depending on current density. In conclusion, experimental observations agree with a model that an increase in current density increases oxygen bubble diameter and decreases bubble residence time within the electrolyzer channel.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Computational Fluid Dynamics Simulations to Support Efficiency Improvements in Aluminum Smelting Process

Smelting is broadly described as the extraction of a metal from its ore. In the United States, aluminum is commonly produced by smelting alumina in bauxite using the Hall-Héroult process. Optimization of equipment and processes in conventional smelting is crucial to enhancing process efficiency and productivity, is necessary for improving the techno-economic feasibility, which directly manifests as the growth of the American economy. To achieve optima, insightful data on the multiphysics phenomena that are inherent to the process must be obtained through physical investigation or high-fidelity numerical simulations. The resolution of relevant scales in time and space for smelting operations requires intensive, high-performance computing (HPC) simulations. Hostile operating conditions limit physical data acquisition to specific techniques; therefore, these data do not describe the multiscale interaction of simultaneous effects. Fortunately, in recent decades, significant advancements in computing hardware and computational methods have made the numerical resolution of such a complex process possible. In this study, a high-fidelity simulation of aluminum smelting was performed using an open-source tool, OpenFOAM, which analyzed many parameters characteristic to underlying phenomena. A multiphysics model based on the Eulerian-Eulerian multifluid approach was adopted. This model can resolve critical issues in the electrolytic smelting of aluminum, such as bubbling of carbon dioxide from the anode(s), magnetohydrodynamics from electromagnetic effects, ionic dissolution of the alumina in the electrolyte, and the evolution of thermal profiles. This study provides valuable connectivity for characteristic data that can direct the future designs of efficient smelters. A basic framework to model and simulate the smelting process using OpenFOAM is presented for user modification in keeping with process development. Of relevance to the flow field, a detailed investigation of vortices produced by bubble motion and electromagnetics is discussed, along with their impact on the evolution of thermal profiles. The predictions show small-scale vortices in the clearance between the anode and cathode caused by magnetic forces. Predictions also indicate relatively large-scale vortices in the inter-anode space resulting from carbon dioxide rising through the electrolytic flow field. The formation of vortices at the edges of anodes was shown to direct alumina charged by the feeder to the bottom of the anodes, thus preventing the entrapment of gas bubbles in the periphery of the bottom of the anode. Symmetry was observed in the location of cold spots in the electrolytic mixture in the vicinity of the feeder. Cold spots were also observed in the clearance between the anode and cathode due to the flow’s transmission of unconverted alumina to this region.

36 MATERIALS SCIENCE↗

NuSTAR broad-band X-ray observation campaign of energetic pulsar wind nebulae in synergy with VERITAS, HAWC and Fermi gamma-ray telescopes

We report recent progress on the on-going NuSTAR observation campaign of 8 TeV-detected middle-aged pulsar wind nebulae (PWNe). This campaign constitutes a major part of our NuSTAR study of some of the most energetic TeV sources in our Galaxy detected by VERITAS and HAWC. NuSTAR is the first focusing X-ray telescope operating above 10 keV in space with sub-arcminute angular resolution. Broad-band X-ray imaging and spectroscopy data, obtained by NuSTAR, allow us to probe sub-PeV electron populations through detecting synchrotron X-ray radiation. Our targets include PeVatron candidates detected by HAWC, the Boomerang nebula, PWNe crushed by supernova remnant shocks (or relic PWNe) and G0.9‚0.1 in the Galactic Center. Combined with Fermi-LAT data and available TeV data, we aim to provide a complete, multi-wavelength view of a diverse class of middle-aged (~10–100 kyrs old) PWNe. Our NuSTAR analysis detected hard X-ray emission from the Eel and Boomerang PWNe and characterized their broad-band X-ray spectra most accurately. We plan to apply both time-evolution and multi-zone PWNe models to multi-wavelength spectral energy distribution (SED) data over the radio, X-ray, GeV and TeV bands. In this proceeding, we will review our observation campaign and discuss the preliminary results for some PWNe.

79 ASTRONOMY AND ASTROPHYSICS↗

Development of an Alternative Approach to Demonstrating Environmental Performance in the UK - 19354

European basic safety standards require that exposure of humans to the potentially harmful effects of ionising radiation are optimised so that they are as low as reasonably achievable, taking account of economic and societal factors. In the United Kingdom the responsibility for ensuring that exposures to humans are optimised is split between two regulatory functions. The Office of Nuclear Regulation regulates exposures to workers in all scenarios and to members of the public in the event of an accident. Environmental regulators in each of the four nations comprising the United Kingdom regulate exposures to members of the public from normal operations. Since the early 1990's, all permissions granted to nuclear sites in the UK for the discharge/disposal of radioactive waste to the environment have contained conditions requiring holders to demonstrate that they minimise the generation of radioactive waste, apply appropriate abatement and discharge/dispose of it in a way that minimises impacts on members of the public and the environment. For many years, the industry standard for providing this demonstration, which was heavily influenced by regulatory expectations and feedback, was to undertake one or a series of multi-attribute decision assessments (MADA). Wood's team of environmental specialists has been involved in undertaking such MADA studies for many years. Since the mid-2000's, our team has become increasingly aware of some of the limitations of undertaking MADA to demonstrate environmental performance for large scale new nuclear build projects and, in particular, the next generation of new nuclear power stations that are being planned and implemented in the UK. We have collaborated with the vendors of reactor technologies, the prospective/owner operators of new nuclear power stations and the developers of new facilities on existing sites to develop an alternative approach to demonstrating environmental performance. Our alternative approach comprises three main pillars which are summarised as: - Evolution - benefit from progressive improvements, operational experience and recent permitting activities. Our alternative approach uses the claim, argument, evidence approach which is commonly used for nuclear safety cases and which allows us to 'tell the story' of how environmental performance has been achieved. We have successfully deployed this approach for all new nuclear power stations proposed in the UK. - Integration - ensure that optimisation is integrated into the project programme and forms part of the 'big picture'. Our alternative approach allows environmental performance to be managed better throughout the life cycle of the project and ensures that our outputs are 'living' documents and do not 'sit on the shelf'. We have successfully demonstrated how this can be applied during rationalisation of major schemes and significant design changes on nuclear new build projects. - Opportunity - identify the best time to deliver elements of the programme. Our alternative approach aims to minimise the overall time, trouble and costs associated with demonstrating environmental performance by ensuring that decisions are made at the time when they offer greatest benefit and by minimising unnecessary rework. Our advice has helped to reduce the project costs and minimise delays associated with regulatory queries and interventions. This paper describes the journey that we have taken with our clients in developing our alternative approach to demonstrating environmental performance. We explain the UK regulatory context and explore the need for change. We present a number of case studies related to new nuclear power stations and other new facilities on existing nuclear sites that demonstrate the successful application of our alternative approach. We provide examples of how we have successfully implemented the outputs of our alternative approach into project and corporate management arrangements. Finally, we examine feedback from clients, regulators and other interested parties to propose future refinements. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

An adaptive scalable fully implicit algorithm based on stabilized finite element for reduced visco-resistive MHD

The magnetohydrodynamics (MHD) equations are continuum models used in the study of a wide range of plasma physics systems, including the evolution of complex plasma dynamics in tokamak disruptions. However, efficient numerical solution methods for MHD are extremely challenging due to disparate time and length scales, strong hyperbolic phenomena, and nonlinearity. Additionally, therefore the development of scalable, implicit MHD algorithms and high-resolution adaptive mesh refinement strategies is of considerable importance. In this work, we develop a high-order stabilized finite-element algorithm for the reduced visco-resistive MHD equations based on the MFEM finite element library (mfem.org). The scheme is fully implicit, solved with the Jacobian-free Newton-Krylov (JFNK) method with a physics-based preconditioning strategy. Our preconditioning strategy is a generalization of the physics-based preconditioning methods in Chacón et al. (2002) to adaptive, stabilized finite elements. Algebraic multigrid methods are used to invert sub-block operators to achieve scalability. A parallel adaptive mesh refinement scheme with dynamic load-balancing is implemented to efficiently resolve the multi-scale spatial features of the system. Our implementation uses the MFEM framework, which provides arbitrary-order polynomials and flexible adaptive conforming and non-conforming meshes capabilities. Results demonstrate the accuracy, efficiency, and scalability of the implicit scheme in the presence of large scale disparity. The potential of the AMR approach is demonstrated on an island coalescence problem in the high Lundquist-number regime (≥ 10 7 ) with the successful resolution of plasmoid instabilities and thin current sheets.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Experimental setup combining in situ hard X-ray photoelectron spectroscopy and real-time surface X-ray diffraction for characterizing atomic and electronic structure evolution during complex oxide heterostructure growth

We describe the next-generation system for in situ characterization of a complex oxide thin film and heterostructure growth by pulsed laser deposition (PLD) using synchrotron hard X-rays. The system consists of a PLD chamber mounted on a diffractometer allowing both real-time surface X-ray diffraction (SXRD) and in situ hard X-ray photoelectron spectroscopy (HAXPES). HAXPES is performed in the incident X-ray energy range from 4 to 12 keV using a Scienta EW4000 electron energy analyzer mounted on the PLD chamber fixed parallel with the surface normal. In addition to the standard application mode of HAXPES for disentangling surface from bulk properties, the increased penetration depth of high energy photoelectrons is used for investigation of the electronic structure changes through thin films grown deliberately as variable thickness capping layers. Such heterostructures represent model systems for investigating a variety of critical thickness and dead layer phenomena observed at complex oxide interfaces. In this new mode of operation, in situ HAXPES is used to determine the electronic structure associated with unique structural features identified by real-time SXRD during thin film growth. The system is configured for using both laboratory excitation sources off-line and on-line operation at beamline 33-ID-D at the Advanced Photon Source. We illustrate the performance of the system by preliminary scattering and spectroscopic data on oxygen vacancy ordering induced perovskite-to-brownmillerite reversible phase transformation in La 2/3 Sr 1/3 MnO 3 films capped with oxygen deficient SrTiO 3–δ (100) layers of varying thickness.

47 OTHER INSTRUMENTATION↗

Wide Band Gap Chalcopyrite Photoelectrodes for Direct Water Splitting (Final Technical Report)

The chalcopyrite material class, typically identified by its most popular alloy CuInGaSe 2 , provides exceptionally good candidates for photoelectrochemical (PEC) water splitting and has the potential to meet DoE EERE’s targets in terms of hydrogen production costs (less than $2/gge). Some key advantages of this class include remarkable photon-to-electron conversion efficiency and a high Faradaic efficiency for the hydrogen evolution reaction, two characteristics essential for efficient PEC water splitting. However, the band gaps of commonly used chalcopyrites in the photovoltaic field (1.0-1.6 eV) are too narrow to be compatible with the multi-junction approach for efficient PEC hydrogen production, in which a stack of solar absorbers generates the bias required for water splitting. Nonetheless, previous studies performed by our team demonstrated that chalcopyrites’ narrow band gaps could be effectively widened using simple conversion steps, leading to functional chalcopyrite-based PEC electrodes with optical band gap in the 1.8-2.4 eV range, making this class highly suitable for renewable hydrogen production via water splitting. This multi-disciplinary research program lead by the University of Hawai’i/Hawai’i Natural Energy Institute combined unique analytical techniques (UNLV), state-of-the-art theoretical modeling (LLNL) with advanced thin film materials synthesis (HNEI, NREL and Stanford) to provide deeper understanding of wide band gap chalcopyrite-based PEC materials and engineer high performance/corrosion-resistant photocathodes with tunable energetics and compatible with the multi-junction approach. The goals of this project were to demonstrate photoelectrochemical (PEC) solar-hydrogen production using a dual absorber system with a solar-to-hydrogen conversion efficiency of at least 15% with an operational life up to 2,000 hours and capable of generating at least 3 liters of hydrogen in 8 hours. After a brief introduction (Section 1) and description of our work plan (Section 2), we present in Section 3 our results on the development of new wide bandgap copper chalcopyrites absorbers for PEC waters splitting. We first show through modeling how alloying can be used to tailor the optical properties and/or surface energetics of various material candidates. We also present how specific defects (e.g., GaCu) can lead to recombination centers within the forbidden gap of copper-poor chalcopyrites. Then, we present our efforts to synthesize high efficiency wide band gap CuGa 3 Se 5 , CuGa(S,Se) 2 and Cu(In,Ga)S 2 photocathodes capable of generating photocurrent density over 10 mA/cm 2 . We also demonstrate that Cu-rich absorbers should be avoided as they lead to poor sub-band gap optical transmission. In Section 4, we first report on our efforts to tune the energetics of chalcopyrites toward the hydrogen evolution reaction. First, we quantified the energetics of wide band gap chalcopyrites interfaced with conventional CdS buffer layer, as measured with X-ray photoelectron spectroscopy techniques, and evidence the presence of a large (and undesirable) conduction band offset at this interface. Then, we highlight some of the work performed with alternative buffer layers, including In 2 S 3 . Durability improvements with various ultra-thin protective layers are presented in Section 5. Our data show that TiO 2 combined with MoS 2 can significantly improve chalcopyrites lifetime up to 350 hours under continuous operation at 8 mA/cm 2 . Finally, in Section 6 we report strategies to integrate chalcopyrite photocathodes into standalone tandem PEC devices. Although promising methods were proposed for both mechanical and monolithic stacking with narrow band gap PV drivers, no functional device was fabricated on time to fulfill the program end goals.

08 HYDROGEN↗

Machine learning pipeline for denoising low signal-to-noise ratio and out-of-distribution transmission electron microscopy datasets

High-resolution transmission electron microscopy (HRTEM) is crucial for observing material’s structural and morphological evolution at Angstrom scales, but the electron beam can alter these processes. Devices such as CMOS-based direct-electron detectors operating in electron-counting mode can be utilized to substantially reduce the electron dosage. However, the resulting images often lead to a low signal-to-noise ratio, which requires frame integration that sacrifices temporal resolution. Several machine learning (ML) models have been recently developed to successfully denoise HRTEM images. Yet, these models are often computationally expensive, and their inference speeds on GPUs are outpaced by the imaging speed of advanced detectors, precluding in situ analysis. Furthermore, the performance of these denoising models on datasets with imaging conditions that deviate from the training datasets has not been evaluated. To mitigate these gaps, we propose a new self-supervised ML denoising pipeline specifically designed for time-series HRTEM images. This pipeline integrates a blind-spot convolution neural network with pre-processing and post-processing steps, including drift correction and low-pass filtering. Results demonstrate that our model outperforms various other ML and non-ML denoising methods in noise reduction and contrast enhancement, leading to improved visual clarity of atomic features. Additionally, the model is drastically faster than U-Net-based ML models and demonstrates excellent out-of-distribution generalization. The model’s computational inference speed is in the order of milliseconds per image, rendering it suitable for application in in-situ HRTEM experiments.

36 MATERIALS SCIENCE↗

Rate Theory Modeling and Simulations of Silicide Fuel at LWR Conditions

Uranium silicide (U 3 Si 2 ) fuel has higher thermal conductivity and higher uranium density, making it a promising candidate for the accident-tolerant fuel (ATF) used in light water reactors (LWRs). However, previous studies on the fuel performance of U 3 Si 2 , including both experimental and computational approaches, have been focusing on the irradiation conditions in research reactors, which usually involve low operation temperatures and high fuel burnups. Thus, it is important to examine the fuel performance of U 3 Si 2 at typical LWR conditions so as to evaluate the feasibility of replacing conventional uranium dioxide fuel with this silicide fuel material. As in-reactor irradiation experiments involve significant time and financial cost, it is appropriate to utilize modeling tools to estimate the behavior of U 3 Si 2 in LWRs based on all those available research reactor experimental references and state-of-the-art density functional theory (DFT) calculation capabilities at the early development stage. Hence, in this report, a comprehensive investigation of the fission gas swelling behavior of U 3 Si 2 at LWR conditions is introduced. The modeling efforts mentioned in this report was based on the rate theory (RT) model of fission gas bubble evolution that has been successfully applied for a variety of fuel materials at devious reactor conditions. Both existing experimental data and DFT-calculated results were used for the optimization of the parameters adopted by the RT model. Meanwhile, the fuel-cladding interaction was captured by the coupling of the RT model with simplified mechanical correlations. Therefore, the swelling behavior of U 3 Si 2 fuel and its consequent interaction with cladding in LWRs was predicted by the rate theory modeling, providing valuable information for the development of U 3 Si 2 fuel as an accident-tolerant alternative for uranium dioxide.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Robust analysis of space-, time-, and energy-resolved soft x-ray measurements of magnetically confined fusion plasmas (invited)

A novel compact multi-energy soft x-ray (ME-SXR) diagnostic based on the PILATUS3 100K x-ray detector has been developed in collaboration between the Princeton Plasma Physics Laboratory and the University of Wisconsin-Madison and tested on the Madison Symmetric Torus (MST) reversed-field pinch. This solid-state photon-counting detector consists of a two-dimensional array of ~100 000 pixels for which the lower photon absorption cutoff energy can be independently set, allowing it to be configured for a unique combination of simultaneous spatial, spectral, and temporal resolution of ~1 cm, 100 eV, and 500 Hz, respectively. The diagnostic is highly versatile and can be readily adapted to diverse plasma operating conditions and scientific needs without any required downtime. New results from improved-confinement and quasi-single helicity plasmas in the MST demonstrate how the detector can be applied to study multiple aspects of the evolution of magnetically confined fusion-grade plasmas. These include observing the evolution of thermal emissivity, characterizing the energy of mid-Z excitation lines, extracting the T e profile, and observing the evolution of non-thermal populations. A technique for integrating the ME-SXR diagnostic into an integrated data analysis framework based on Bayesian inference is also presented. As a result, this allows ME-SXR measurements to be combined with data for complementary diagnostics in order to simultaneously infer Te and nZ from all available information.

47 OTHER INSTRUMENTATION↗

Build Orientation Dependent Microstructure in Polymer Laser Sintering: Relationship to Part Performance and Evolution with Aging

Laser sintering (LS) is widely used to produce functional polymeric parts; however, the resulting parts are often limited by their porous structure, and performance of the part may be strongly anisotropic. Relating the structural features of parts to build process conditions or powder feedstock has been explored previously. In contrast, little is known regarding how the unique internal structures of LS parts evolve and relate to their performance later in their life cycle, for example, after use in a real-world operating environment. In this study, a tightly controlled LS build process and measurement campaign by standard X-ray computed tomography (XCT), supported by high-resolution synchrotron XCT, was used to benchmark the internal microstructure (e.g. porosity) as a function of four different build orientations in printed polyamide-12 (PA-12) parts. The initial performance of the parts after printing was characterized by tensile testing and dynamic mechanical analysis (DMA). Arrays of PA-12 parts in different build orientations were exposed to steam (under pressure) and air across multiple temperature and time points for the purposes of accelerated aging through oxidative and hydrolytic breakdown. Exposing parts to steam dramatically altered the internal microstructure and functional properties such as the glass transition temperature, tensile properties, and damping behavior. Notably, post-aging XCT revealed large microstructural changes after only 40 h of steam treatment relative to the as-printed specimens. Furthermore, pore reorganization and changes in crystallinity occurred regardless of whether the steam temperature was aggressive enough to induce a significant loss in mechanical properties. The build orientation dependence on the aging rate was minimal with the relative trend in performance persisting across most metrics among the different orientations even after aging.

36 MATERIALS SCIENCE↗

Experimental Limit on Nonlinear State-Dependent Terms in Quantum Theory

Linear time evolution is one of the fundamental postulates of quantum theory. Past theoretical attempts to introduce nonlinearity into quantum evolution have violated causality. However, a recent theory has introduced nonlinear state-dependent terms in quantum field theory, preserving causality [D. E. Kaplan and S. Rajendran, Phys. Rev. D 105, 055002 (2022)]. We report the results of an experiment that searches for such terms. Our approach, inspired by the Everett many-worlds interpretation of quantum theory, correlates a binary macroscopic classical voltage with the outcome of a projective measurement of a quantum bit, prepared in a coherent superposition state. Measurement results are recorded in a bit string, which is used to control a voltage switch. Presence of a nonzero voltage reading in cases of no applied voltage is the experimental signature of a nonlinear state-dependent shift of the electromagnetic field operator. We implement blinded measurement and data analysis with three control bit strings. Control of systematic effects is realized by producing one of the control bit strings with a classical random-bit generator. The other two bit strings are generated by measurements performed on a superconducting qubit in an IBM Quantum processor and on a N 15 nuclear spin in a nitrogen-vacancy center in diamond. Our measurements find no evidence for electromagnetic quantum state-dependent nonlinearity. We set a bound on the parameter that quantifies this nonlinearity | ε γ | < 4.7 × 10 - 11 , at 90% confidence level.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Radiation damage effects in beryllium for next generation neutrino beam targetry (Final Technical Report)

Current and future high-power accelerators put severe requirements on materials used for target and beam windows and target facilities have been recognized as a critical challenge in development of future particle accelerators. In accelerators, window and target materials are exposed to extreme conditions, which include bombardment with very high energy protons (1- 100 GeV) and thermomechanical shock waves. Radiation can cause direct damage in the material, and it leads to production of transmutation products (especially helium), both phenomena having a potential adverse effect on the stability and durability of the target/window material. At high enough temperatures, He can aggregate to form gas bubbles, which in turn cause significant dimensional changes (swelling), enable easy crack propagation, and eventually cause failure by fracture. On the other hand, if the temperature is too low, radiation damage accumulates in the form of internal defects (e.g., dislocations), leading to hardening and a decreased ductility of the material. In this project, we will focus on beryllium since it is considered to be one of the candidate materials for beam windows and targets in the next-generation proton accelerators, e.g., the Long Baseline Neutrino Facility (LBNF). Radiation effects in Be have been studied in the context of nuclear fusion reactor applications. However, key differences exist between reactor and accelerator conditions, including neutron vs. proton irradiation, continuous vs. pulsed beam flux, much higher energies of bombarding particles in accelerators, and higher operating temperatures for typical reactors. For example, the impact of beam pulsing on the radiation damage and the He bubble kinetics is largely unknown. While results obtained on Be from fusion research might not be directly transferrable to understanding target materials, there is an opportunity to bring state-of-the-art tools from materials research in nuclear reactors to aid design of target and beam window materials in high-power accelerators. To this end, the overarching goal of this project are to develop an experimentally-validated computational framework capable of predicting radiation damage evolution in beryllium relevant to beam window and target conditions, focusing on He bubble formation and growth as a function of irradiation temperature. Our model will be based on the cluster dynamics formalism, where size distribution of defects and He bubbles is simulated as a function of time, temperature, and radiation dose. Parameters for the model will be taken from published experiments and from high-fidelity atomistic simulations proposed in this project. In addition, we will carry out a series of targeted ex-situ and in-situ dual-beam experiments using low-energy protons to provide critical data for validation of the model on the effects of radiation on He clustering, He bubble distribution, and dislocation loop density/size in proton irradiated Be.

36 MATERIALS SCIENCE↗

Inertia estimation for power grids: A review of methods, challenges, and future prospects

The electric power grid is undergoing a significant transformation, shifting from traditional synchronous generators to inverter-based resources (IBRs) such as solar photovoltaics, wind turbines, and energy storage systems. This evolution leads to a reduction in system inertia, a critical attribute for maintaining frequency stability in response to disturbances. Consequently, the ability to monitor and estimate system inertia has become increasingly essential. This paper provides a comprehensive review of existing inertia estimation methodologies, analyzing them from multiple perspectives, including the types of data utilized, underlying estimation principles, operational modes, and system-wide applicability. A comparative summary table is included to distill commonalities and key characteristics across various studies. In addition, the paper examines practical implementations of inertia estimation across several major power systems worldwide, including the U.S. interconnections, the Nordic power system, and the U.K. grid. Key challenges are identified, particularly in estimating contributions from virtual inertia sources and load-induced inertia in increasingly converter-dominated networks. To address these emerging challenges, the paper proposes an integrated framework for real-time inertia estimation and monitoring. This framework encompasses critical components such as data acquisition, inertia estimation from both synchronous and non-synchronous sources, load-induced effects, optimization techniques, forecasting, and virtual inertia scheduling. Collectively, these elements enable dynamic, system-wide monitoring and adaptive control of grid inertia.

Inertia estimation↗