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At least 1,207 records · Page 67

Investigating ceramic breeder pebble beds thermomechanics evolution using novel pressure mapping technology

Ceramic breeder pebble beds undergo complex thermomechanical interactions during blanket operation due to stress build-up and relaxation under the effects of confined thermal expansion, thermal cycling, and creep. Understanding the evolution of such processes can aid in guiding blanket design/assembly, breeder materials developments, predicting performance and possible failure modes. This study introduces experimental techniques that enable us to create an environment in which the pebble bed stresses are organically generated as a result of relevant temperature gradients and magnitudes that allows us to observe the combined thermomechanical interaction effects. A novel non-intrusive in-situ tactile pressure sensing technology is used to generate real-time contact pressure maps revealing the spatial and temporal stress evolution with emphasis on understanding the roles that each of the thermo-mechanical forces play in dictating the pebble bed’s equilibrium conditions. Two types of bed-wall contact pressure drop were recorded: (1) within the subsequent cycles due to pebbles irreversible rearrangements, and (2) within the cycle itself as a result of creep/stress-relaxation. Consequently, by the fourth cycle, the contact pressure drops to negligible values and remains stable. This stability is attributed to two modes of self-regulation: (1) stress self-regulation as a result of pressure rise and fall due to thermal expansion and creep/thermal cycling, respectively, and (2) temperature self-regulation due to the locally enhanced thermal conductivity in the core region of the bed accompanied by deteriorated interface conductance. These two mechanisms are desirable as they lower the probability of the events of pebbles crushing and thermal runaways under high temperatures/stresses and poor heat extraction.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

An efficient quantum circuit for block encoding a pairing Hamiltonian

We present an efficient quantum circuit for block encoding a pairing Hamiltonian often studied in nuclear physics. Our block encoding scheme does not require mapping the creation and annihilation operators to the Pauli operators and representing the Hamiltonian as a linear combination of unitaries. Instead, we show how to encode the Hamiltonian directly using controlled swap operations. We analyze the gate complexity of the block encoding circuit and show that it scales polynomially with respect to the number of qubits required to represent a quantum state associated with the pairing Hamiltonian. We also show how the block encoding circuit can be combined with the quantum singular value transformation to construct an efficient quantum circuit for approximating the density of states of a pairing Hamiltonian. The techniques presented can be extended to encode more general second-quantized Hamiltonians.

97 MATHEMATICS AND COMPUTING↗

110th Anniversary : Thermal Coupling via Heat Transfer: A Potential Route to Simple Distillation Configurations with Lower Heat Duty

Numerous configurations are available for the separation of a multicomponent mixture by distillation; each of which has different energy requirements. Here, we classify heat integration (a valuable method of reducing energy requirements) within distillation into two categories: conventional thermal coupling with mass exchange between columns (TCM) and thermal coupling via heat transfer without mass exchange (TCH). The sharp split distillation configurations, with the lowest number of distillation sections and transfer streams, provide simple distillation configurations but are known to have heat duties that are much higher than the fully thermally coupled (FTC) or Petlyuk configuration. However, for a mixture with four or more components, FTC, having the maximum number of column sections, is a complex configuration to build and operate. Through specific examples of four and five component distillations, we present, for the first time, sharp split configurations, using only one TCH and no TCM, which have a lower heat duty than the corresponding FTC containing only TCM, without requiring substantial pressure changes in the system.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Light-Driven Redox Activation of CO 2 - and H 2 -Activating Complexes in a Self-Assembled Triad

We report a self-assembled triad for artificial photosynthesis composed of a chromophore, carbon-dioxide reduction catalyst, and hydrogen oxidation complex, which is designed to operate without conventional sacrificial redox equivalents. Excitation of the zinc-porphyrin chromophore of the triad results in ultrafast charge transfer between a tungsten-alkylidyne donor and a rhenium diimine tricarbonyl acceptor, producing a charge-separated state that persists on the time scale of tens of nanoseconds and is thermodynamically capable of the primary dihydrogen and carbon dioxide binding steps for initiating the reverse water-gas shift reaction. The charge-transfer behavior of this system was probed using transient absorption spectroscopy in the visible, near-infrared, and mid-infrared spectral regions. Here, the behavior of the triad was compared with that of the zinc-porphyrin-rhenium-diimide dyad; the triad was found to have a significantly longer charge-separated lifetime than other previously reported porphyrin-rhenium diimine compounds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Universal scaling laws of keyhole stability and porosity in 3D printing of metals

Metal three-dimensional (3D) printing includes a vast number of operation and material parameters with complex dependencies, which significantly complicates process optimization, materials development, and real-time monitoring and control. We leverage ultrahigh-speed synchrotron X-ray imaging and high-fidelity multiphysics modeling to identify simple yet universal scaling laws for keyhole stability and porosity in metal 3D printing. The laws apply broadly and remain accurate for different materials, processing conditions, and printing machines. We define a dimensionless number, the Keyhole number, to predict aspect ratio of a keyhole and the morphological transition from stable at low Keyhole number to chaotic at high Keyhole number. Furthermore, we discover inherent correlation between keyhole stability and porosity formation in metal 3D printing. By reducing the dimensions of the formulation of these challenging problems, the compact scaling laws will aid process optimization and defect elimination during metal 3D printing, and potentially lead to a quantitative predictive framework.

42 ENGINEERING↗

Mechanistic Investigation of Redox Processes in Zn-MnO2 battery in Mild Aqueous Electrolytes

Zinc-MnO2 based batteries have acquired attention for grid-level applications, due to impressive theoretical performance, cost effectiveness and intrinsic safety. However, there are still many challenges that remain elusive due to the complex and controversial mechanisms of operation that hinders commercialization. In this work, the detailed redox processes that occur at the cathode during Zn-MnO2 battery operation are elucidated. Using a blend of structural and electrochemical techniques, the redox pairs that occur during operation are mechanistically studied while also showcasing the true impact of the electrolyte additive (0.1 M MnSO4) in a 1 M ZnSO4 electrolyte. An electrochemical quartz-crystal microbalance (EQCM) has been leveraged to reveal the effect of zinc hydroxy sulfate salt (Zn4SO4(OH)6·nH2O) and zinc manganese oxide (ZnxMnyOz) dissolution/deposition, which are believed to be major components during discharge and charge conditions. . These results provide insight not currently available, allowing a holistic view of the electrochemical reaction mechanisms during battery operation.

Rodriguez Perez, Ismael A.↗

Methods of improving spatial resolution for IR spectroscopy in atmospheric-pressure plasma systems

High-temperature, atmospheric pressure plasma systems operated in molecular gases present complex diagnostic challenges. Infrared spectroscopy has been used to make measurements of the absorbance spectrum of complex molecular gas mixtures and thereby calculate the concentrations and species temperatures in these systems. For atmospheric-pressure systems, high spatial gradients arise and high spatial-resolution measurements are thus desirable. Some systems have achieved increased spatial resolution by reducing the beam diameter. However, this increase in spatial resolution comes at the expense of the optical throughput. Here we propose modifying a commercial Fourier Transform, Infrared spectrometer system with a set of simple optical elements. This design allows for scannable, high spatial resolution absorbance spectrum measurements of a complex molecular gas mix. We analyze the signal-to-noise ratio for this design and compare it with the diameter reduction method. For sufficiently low plasma radiation levels, this design improves the signal-to-noise ratio relative to reducing the beam diameter size while transmitting nearly all of the beam power. Furthermore, whether this design can achieve the desired sub-mm spatial resolution depends on the radiating area of the infrared light source in the spectrometer.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

An Integrated Risk Assessment Process of Safety-Related Digital I&C Systems in Nuclear Power Plants

Upgrading the existing analog instrumentation and control (I&C) systems to state-of-the-art digital I&C (DI&C) systems will greatly benefit existing light water reactors. However, the issue of software common cause failure (CCF) remains an obstacle in terms of qualification for digital technologies. Existing analyses of CCFs in I&C systems mainly focus on hardware failures. With the application and upgrading of new DI&C systems, design flaws could cause software CCFs to become a potential threat to plant safety, considering that most redundancy designs use similar digital platforms or software in their operating and application systems. With complex multilayer redundancy designs to meet the single failure criterion, these I&C safety systems are of particular concern in U.S. Nuclear Regulatory Commission licensing procedures. In Fiscal Year 2019, the Risk-Informed Systems Analysis (RISA) Pathway of the U.S. Department of Energy’s Light Water Reactor Sustainability Program initiated a project to develop a risk assessment strategy for delivering a strong technical basis to support effective, licensable, and secure DI&C technologies for digital upgrades and designs. An integrated risk assessment for the DI&C process was proposed for this strategy to identify potential key digital-induced failures, implement reliability analyses of related digital safety I&C systems, and evaluate the unanalyzed sequences introduced by these failures (particularly software CCFs) at the plant level. Here this paper summarizes these RISA efforts in the risk analysis of safety-related DI&C systems at Idaho National Laboratory.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Scintillator ageing of the T2K near detectors from 2010 to 2021

The T2K experiment widely uses plastic scintillator as a target for neutrino interactions and an active medium for the measurement of charged particles produced in neutrino interactions at its near detector complex. Over 10 years of operation the measured light yield recorded by the scintillator based subsystems has been observed to degrade by 0.9–2.2% per year. Extrapolation of the degradation rate through to 2040 indicates the recorded light yield should remain above the lower threshold used by the current reconstruction algorithms for all subsystems. This will allow the near detectors to continue contributing to important physics measurements during the T2K-II and Hyper-Kamiokande eras. Additionally, work to disentangle the degradation of the plastic scintillator and wavelength shifting fibres shows that the reduction in light yield can be attributed to the ageing of the plastic scintillator. The long component of the attenuation length of the wavelength shifting fibres was observed to degrade by 1.3–5.4% per year, while the short component of the attenuation length did not show any conclusive degradation.

47 OTHER INSTRUMENTATION↗

Outlook towards deployable continual learning for particle accelerators

Particle accelerators are high power complex machines. To ensure uninterrupted operation of these machines, thousands of pieces of equipment need to be synchronized, which requires addressing many challenges including design, optimization and control, anomaly detection and machine protection. With recent advancements, machine learning (ML) holds promise to assist in more advance prognostics, optimization, and control. While ML based solutions have been developed for several applications in particle accelerators, only few have reached deployment and even fewer to long term usage, due to particle accelerator data distribution drifts caused by changes in both measurable and non-measurable parameters. In this paper, we identify some of the key areas within particle accelerators where continual learning can allow maintenance of ML model performance with distribution drifts. Particularly, we first discuss existing applications of ML in particle accelerators, and their limitations due to distribution drift. Next, we review existing continual learning techniques and investigate their potential applications to address data distribution drifts in accelerators. By identifying the opportunities and challenges in applying continual learning, this paper seeks to open up the new field and inspire more research efforts towards deployable continual learning for particle accelerators.

43 PARTICLE ACCELERATORS↗

Neural network based analysis of multimodal bond distributions using extended x-ray absorption fine structure spectra

Knowledge of the local coordination environment around atomic species in functional materials is critical for understanding their mechanisms of operation. Heterogeneous mixtures of metal complexes are ubiquitous in catalysts, ionic liquids, molten salts, biological enzymes, and geochemical systems, among many others. Extracting information from ensemble-average measurements about the structural and compositional descriptors of each type of coordination complex comprising the mixture is not generally possible, especially when they possess multimodal bond-length distributions. Here, we developed a method that enables the mapping of an x-ray absorption spectrum on the radial distribution function describing the average environment of the metal ions. The supervised neural network based method utilizes an objective training set, for which the choice of the local structural motifs is completely agnostic to the theoretically expected structure and dynamics of the modeled system. The method was validated using first-principles modeling of structural dynamics of nickel complexation in molten salts, and it applies to a large class of heterogeneous systems, including those studied under in situ and operando conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Signal-preserving CMB component separation with machine learning

Analysis of microwave sky signals, such as the cosmic microwave background, often requires component separation using multifrequency methods, whereby different signals are isolated according to their different frequency behaviors. Many so-called blind methods, such as the internal linear combination (ILC), make minimal assumptions about the spatial distribution of the signal or contaminants, and only assume knowledge of the frequency dependence of the signal. The ILC produces a minimum-variance linear combination of the measured frequency maps. In the case of Gaussian, statistically isotropic fields, this is the optimal linear combination, as the variance is the only statistic of interest. However, in many cases the signal we wish to isolate, or the foregrounds we wish to remove, are non-Gaussian and/or statistically anisotropic (in particular for the case of Galactic foregrounds). In such cases, it is possible that machine learning (ML) techniques can be used to exploit the non-Gaussian features of the foregrounds and thereby improve component separation. However, many ML techniques require the use of complex, difficult-to-interpret operations on the data. We propose a hybrid method whereby we train an ML model using only combinations of the data that , and combine the resulting ML-predicted foreground estimate with the ILC solution to reduce the error from the ILC. We demonstrate our methods on simulations of extragalactic temperature and Galactic polarization foregrounds and show that our ML model can exploit non-Gaussian features, such as point sources and spatially varying spectral indices, to produce lower-variance maps than ILC—e.g., reducing the variance of the B-mode residual by factors of up to 5—while preserving the signal of interest in an unbiased manner. Moreover, we often find improved performance even when applying our ML technique to foreground models on which it was not trained. Published by the American Physical Society 2025

McCarthy, Fiona (ORCID:0000000253893565)↗

Diagnosis of Factors Impacting Yield in Multilayer Devices for Superconducting Electronics

The ability to localize defects in order to understand failure mechanisms in complex superconducting electronics circuits, while operating at low temperature, does not yet exist. Here, this work applies thermally-induced voltage alteration (TIVA), to a biased superconducting electronics (SCE) circuit at ambient temperature. TIVA is a commonly used, laser-based failure analysis technique developed for silicon-based microelectronics. The non-operational circuit consisted of an arithmetic logic unit (ALU) in a high-frequency test bed designed at HYPRES and fabricated by MIT Lincoln Laboratory using their SFQ5ee process. Localized TIVA signals were correlated with reflected light images at the surface, and these sites were further investigated by scanning electron microscopy imaging of focused ion-beam cross-sections. The areas investigated, where prominent TIVA signals were observed, showed seams in the Nb wiring layers at contacts to Josephson junctions or inductors and/or disrupted junction morphologies. Finally, these results suggest that the TIVA technique can be used at ambient temperature to diagnose fabrication defects that may cause low temperature circuit failure.

36 MATERIALS SCIENCE↗

Toward a Fully Integrated Multiphysics Simulation Framework for Fusion Blanket Design

Fusion is an attractive clean-energy solution, thanks to its various advantages, such as reduced radioactivity, little high-level nuclear waste, ample fuel supplies, and increased safety. However, the harsh operating environment introduced by a complex fusion plasma system makes design and integration of fusion blankets incredibly challenging and time-consuming. This work focuses on developing a fully integrated multiphysics simulation framework based on an advanced open-source platform—the Multiphysics Object-Oriented Simulation Environment (MOOSE)—to alleviate the difficulties in fusion blanket design and integration. MOOSE is a massively parallel finite element/volume multiphysics simulation platform that has been widely adopted within the nuclear fission community. Even though fission and fusion are fundamentally different, they involve similar multiphysics phenomena. A fully integrated open-source multiphysics simulation framework tailored for the fusion blanket design will be implemented by leveraging the well-established multiphysics capabilities in MOOSE. Once successfully developed, this fully integrated framework will rapidly evaluate a blanket design concept and offer insights for subsequent iterations. As the first step, we will mainly aim to integrate neutronics analysis, system thermal hydraulics simulation, and full 3-D heat transfer calculations. The efficacy of the integrated framework will be verified using an innovative solid ceramic blanket design. While the project’s final goal is to enable a fully integrated multiphysics simulation platform for various fusion blanket concepts, here this work, as a preliminary step, will mainly focus on a solid ceramic breeder helium-cooled blanket.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Fast All-sky Radiation Model for Solar applications (FARMS) [SWR-16-18]

The Fast All-sky Radiation Model for Solar applications (FARMS) is used to compute cloudy irradiance. Radiative transfer (RT) models simulating broadband solar radiation have been widely used by atmospheric scientists to model solar resources for various energy applications such as operational forecasting. Due to the complexity of solving the RT equation, the computation under cloudy conditions can be extremely time consuming though many approximations (e.g. two-stream approach and delta-M truncation scheme) have been utilized. Thus, a more efficient RT model is crucial for model developers as a new option for approximating solar radiation at the land surface with minimal loss of accuracy. We have developed a fast all-sky radiation model for solar applications (FARMS) using the simplified clear-sky RT model, REST2, and simulated cloud transmittances and reflectances from the Rapid Radiation Transfer Model (RRTM) with a sixteen-stream Discrete Ordinates Radiative Transfer (DISORT). Simulated lookup tables (LUTs) of cloud transmittances and reflectances were created by varying cloud optical thicknesses, cloud particle sizes, and solar zenith angles. Equations with optimized parameters were fitted to the cloud transmittances and reflectances to develop the model. Using this model the all-sky solar irradiance at the land surface can be computed rapidly by combining REST2 with the cloud transmittances and reflectances. This new RT model is more than 1000 times faster than those currently utilized in solar resource assessment and forecasting since it does not explicitly solve the RT equation for each individual cloud condition. Our results indicate the accuracy of the fast radiative transfer model is comparable to or better than two-stream approximation in term of computing cloud transmittance and solar radiation.

Xie, Yu↗

INTEGRATED RISK ASSESSMENT OF DIGITAL I&C SAFETY SYSTEMS FOR NUCLEAR POWER PLANTS

Upgrading the existing analog instrumentation and control (I&C) systems to state-of-the-art digital I&C (DI&C) systems provides the foremost means to improve performance and reduce costs for existing light-water reactors (LWRs). However, qualification of digital technologies remains a challenge?especially the issue of software common cause failure (CCF), which has been difficult to address. Existing analyses of CCFs in I&C systems mainly focus on hardware failures. With the application and upgrading of new DI&C systems, software CCFs due to design flaws might become a potential threat to plant safety, considering that most redundancy designs use similar digital platforms or software in their operating and application systems. With complex multi-layer redundancy designs to meet the single failure criterion, these I&C safety systems are of particular concern in U.S. Nuclear Regulatory Commission (NRC) licensing procedures. In 2019, the Risk-Informed Systems Analysis (RISA) Pathway of the U.S. Department of Energy?s (DOE?s) Light Water Reactor Sustainability (LWRS) Program initiated a project to develop a risk assessment strategy for delivering a strong technical basis to support effective, licensable, secure DI&C technologies for digital upgrades/designs. An integrated risk assessment for the DI&C (RADIC) process was proposed for this strategy to identify potential key digital-induced failures, implement reliability analyses of related digital safety I&C systems, and evaluate the unanalyzed sequences introduced by these failures (particularly software CCFs) at the plant level. This paper summarizes these RISA efforts in the risk analysis of safety-related DI& systems at Idaho National Laboratory.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

IOTA experiment for proton pulse compression at extreme space-charge

A gammaT scheme may be required for the PIP-II era performance or ACE-MIRT era performance of the Booster. PIP-II era operations of the Fermilab proton complex will require the Fermilab Booster to increase beam intensity from 4.5e12 to 6.5e12 protons, while also increasing its ramp from 15 Hz to 20 Hz. These changes pose particular challenges for transition-crossing in the Booster, where longitudinal beam quality must be controlled in order to facilitate slip-stacking in the Recycler Ring later in the Main Injector cycle. Two novel gammaT jump schemes are proposed, termed “double gammaT jump” and “partial gammaT jump”, which optimize the magnitude of the gammaT jump within optics and power supply constraints.

Eldred, Jeffrey [Fermilab]↗

ON THE WAY TO A 10MEV, CONDUCTION-COOLED COMPACT SRF ACCELERATOR

After the success of designing a compact 1MeV, 1MW accelerator based on conduction-cooled SRF, Jefferson Lab is now pursuing a concept to provide a tenfold increase of the beam energy. The obvious challenge for SRF is to move from a single-cell to a multicell cavity while maintaining high efficiency and the ability to operate the machine without a complex cryogenic plant. This paper summarizes the current state of this effort with respect to the design of a Nb3Sn coated five-cell cavity and the corresponding RF components, especially the fundamental power coupler (FPC), as well as first thermal analysis of the cryocooler-based cooling setup.

Ciovati, G.↗