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At least 235 records · Page 13

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DOE OSTI2020

Computationally efficient evaluation of optimum homogeneous charge compression ignition operating range with accelerated multizone engine cycle simulation

The very intensive calculations necessary to define a performance map requiring evaluation of over a hundred individual operating points can be efficiently conducted with accelerated multizone for engine cycle simulation, leading to a definition of regions of acceptable and optimum homogeneous charge compression ignition operation. Accelerated multizone for engine cycle simulation has the virtue of enabling accurate evaluation of many operating conditions based on thermal stratification data from a single fluid mechanics run at motored conditions. This is possible because thermal stratification is more sensitive to engine geometry than to operating conditions. In this article, accuracy of accelerated multizone for engine cycle simulation is demonstrated by comparison with experimental data for iso-octane homogeneous charge compression ignition operation over a broad range of lean equivalence ratios (0.14–0.28). The validated accelerated multizone for engine cycle simulation model is then applied to generating a performance map for an engine controlled by appropriately adjusting equivalence ratio and internal exhaust gas recirculation. Regions of acceptable and optimum combustion are identified. It is finally demonstrated that while indicated mean effective pressure remains low for optimum homogeneous charge compression ignition operation (1–4 bar), this is sufficient for a large fraction of typical driving in light-duty vehicles. Much driving including idle can therefore be done in homogeneous charge compression ignition mode at high efficiency and low (essentially zero) NOx and particulate matter emissions.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2024

Automated Grain Boundary (GB) Segmentation and Microstructural Analysis in 347H Stainless Steel Using Deep Learning and Multimodal Microscopy

Austenitic 347H stainless steel offers superior mechanical properties and corrosion resistance required for extreme operating conditions such as high temperature. The change in microstructure due to composition and process variations is expected to impact material properties. Identifying microstructural features such as grain boundaries thus becomes an important task in the process-microstructure-properties loop. Applying convolutional neural network (CNN)-based deep learning models is a powerful technique to detect features from material micrographs in an automated manner. In contrast to microstructural classification, supervised CNN models for segmentation tasks require pixel-wise annotation labels. However, manual labeling of the images for the segmentation task poses a major bottleneck for generating training data and labels in a reliable and reproducible way within a reasonable timeframe. Microstructural characterization especially needs to be expedited for faster material discovery by changing alloy compositions. Here, in this study, we attempt to overcome such limitations by utilizing multimodal microscopy to generate labels directly instead of manual labeling. We combine scanning electron microscopy images of 347H stainless steel as training data and electron backscatter diffraction micrographs as pixel-wise labels for grain boundary detection as a semantic segmentation task. The viability of our method is evaluated by considering a set of deep CNN architectures. We demonstrate that despite producing instrumentation drift during data collection between two modes of microscopy, this method performs comparably to similar segmentation tasks that used manual labeling. Additionally, we find that naïve pixel-wise segmentation results in small gaps and missing boundaries in the predicted grain boundary map. By incorporating topological information during model training, the connectivity of the grain boundary network and segmentation performance is improved. Finally, our approach is validated by accurate computation on downstream tasks of predicting the underlying grain morphology distributions which are the ultimate quantities of interest for microstructural characterization.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Experimental signatures of electron cyclotron wave energy condensation in magnetic islands

Here, bifurcation of the electron temperature perturbation (ΔT e ) in magnetic islands due to electron cyclotron current drive (ECCD) is reported for the first time in toroidal plasmas. In this DIIID experiment ΔT e spontaneously increases by 50% in a growing 2,1 island which in turn rapidly shrinks, consistent with improved stabilization by the ECCD due to the temperature bifurcation. This non-linearity of ΔT e maps out a hysteresis in the island evolution cycle, in qualitative agreement with the theoretically predicted radio frequency current condensation effect. Therefore, this observed bifurcation can be critical for the avoidance of disruptions caused by tearing modes in tokamaks.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Revealing the structure of light pseudoscalar mesons at the electron–ion collider

The questions of how the bulk of the Universe's visible mass emerges and how it is manifest in the existence and properties of hadrons are profound, and probe the heart of strongly interacting matter. Paradoxically, the lightest pseudoscalar mesons appear to be key to a further understanding of the emergent mass and structure mechanisms. These mesons, namely, the pion and kaon, are the Nambu-Goldstone boson modes of quantum chromodynamics (QCD). Unravelling their partonic structure and the interplay between emergent and Higgs-boson mass mechanisms is a common goal of three interdependent approaches - continuum QCD phenomenology, lattice-regularised QCD, and the global analysis of parton distributions - linked to experimental measurements of hadron structure. Experimentally, the anticipated electron-ion collider will enable a revolution in our ability to study pion and kaon structures, accessed by scattering from the 'meson cloud' of the proton through the Sullivan process. With the goal of enabling a suite of measurements that can address these questions, we examine key reactions that identify the critical detector-system requirements needed to map tagged pion and kaon cross-sections over a wide range of kinematics. The excellent prospects for extracting pion structural, functional, and form-factor data are outlined, and similar prospects for kaon structures are discussed in the context of a worldwide programme. Finally, the successful completion of the programme outlined herein will deliver deep, far-reaching insights into the emergence of pions and kaons, their properties, and their role as QCD's Goldstone boson modes.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

Application of Shift Ex-Core Calculations to a Detailed MSR Model

This report documents the collaborative research conducted between Argonne National Laboratory (ANL) and Oak Ridge National Laboratory (ORNL) on applying the Monte Carlo neutronics code Shift to calculate the radiation dose rates for a detailed molten salt reactor (MSR) model based on the Molten Salt Breeder Reactor (MSBR). In this work scope, the ANL and ORNL teams worked together and applied Shift to calculate the radiological environments of this detailed MSR facility modeled with explicit geometries. The radiological conditions within the MSR facility were modeled for when the reactor is at two different operation modes: normal full power and drained state. The FW-CADIS hybrid method in Shift was applied successfully to calculate the ex-core neutron and gamma dose rates for the MSBR at full power. Dose rate maps showed that in the current MSBR numerical model, potential pathways exist for neutrons and gammas to stream through the 8-foot concrete shield to reach the top of the MSBR reactor cell. Neutron and gamma dose rates within the drain cell were also calculated for the MSBR at the drained state by integrating the source terms obtained from an ORIGEN-S depletion calculation into the Shift simulation. The results indicate that in the drained state, the delayed gammas from the depleted fuel salt are the main contributors to the dose rates, which suggests that a steel liner in the tank model must be added for calculating the dose rates in the drain cell.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2024

VpROM: a novel variational autoencoder-boosted reduced order model for the treatment of parametric dependencies in nonlinear systems

Reduced Order Models (ROMs) are of considerable importance in many areas of engineering in which computational time presents difficulties. Established approaches employ projection-based reduction, such as Proper Orthogonal Decomposition. The limitation of the linear nature of such operators is typically tackled via a library of local reduction subspaces, which requires the assembly of numerous local ROMs to address parametric dependencies. Our work attempts to define a more generalisable mapping between parametric inputs and reduced bases for the purpose of generative modeling. We propose the use of Variational Autoencoders (VAEs) in place of the typically utilised clustering or interpolation operations, for inferring the fundamental vectors, termed as modes, which approximate the manifold of the model response for any and each parametric input state. The derived ROM still relies on projection bases, built on the basis of full-order model simulations, thus retaining the imprinted physical connotation. However, it additionally exploits a matrix of coefficients that relates each local sample response and dynamics to the global phenomena across the parametric input domain. The VAE scheme is utilised for approximating these coefficients for any input state. This coupling leads to a high-precision low-order representation, which is particularly suited for problems where model dependencies or excitation traits cause the dynamic behavior to span multiple response regimes. Moreover, the probabilistic treatment of the VAE representation allows for uncertainty quantification on the reduction bases, which may then be propagated to the ROM response. The performance of the proposed approach is validated on an open-source simulation benchmark featuring hysteresis and multi-parametric dependencies, and on a large-scale wind turbine tower characterised by nonlinear material behavior and model uncertainty.

Conditional VAEs↗

DOE OSTI2021

Simultaneous mapping of nanoscale dielectric, electrochemical, and ferroelectric surface properties of van der Waals layered ferroelectric via advanced SPM

Ferroelectric surfaces involve a complex interplay between polarization and dielectric properties, internal and external surface charge screening, and ionic and electrochemical effects. There is currently no good way to simultaneously capture all the required information at appropriate length scales. To this end, we present an advanced scanning probe microscopy approach for simultaneously mapping surface potential, dielectric, and piezoelectric properties on the nanoscale. For quantitatively mapping electromechancial properties, we utilize interferometric displacement sensing piezoresponse force microscopy, which measures the effective piezoelectric coefficient free of background artifacts such as the cantilever body electrostatics. The dielectric and surface electrochemical properties are captured during G-mode electrostatic force microscopy/Kelvin probe force microscopy operated in the lift mode. We show the capabilities of this approach on the chemically phase separated composite sample consisting of a van der Waals layered ferroelectric CuInP 2 S 6 phase and a non-polar In 4/3 P 2 S 6 phase. Finally, we demonstrate domain structure evolution during thermally stimulated phase transition.

36 MATERIALS SCIENCE↗

DOE OSTI2026

A Methodology to Evaluate the Grid Reliability Impact of Oscillations Induced by Large Loads

The rapid growth of hyperscale AI data centers is bringing renewed attention to the reliability risk that sustained forced oscillations pose to bulk power systems, with cyclic computational workloads emerging as a new forcing source. Unlike the broadband, stochastic disturbances from traditional industrial loads such as arc furnaces, AI training and inference facilities can inject large active power swings concentrated at specific frequencies over extended durations - characteristics that existing grid planning practices do not account for. While the North American Electric Reliability Corporation (NERC) has recognized this gap and called for system-level studies of large load interconnections, no standardized methodology exists to screen, simulate, and quantify these risks at the planning stage. This report presents the Risk Assessment Tool for Large Load-induced Events (RATLLE), a Python-based, publicly available script suite developed at the Pacific Northwest National Laboratory to evaluate bulk power system reliability risks from data center-induced oscillations. RATLLE implements a three-module workflow: a screening module that identifies vulnerable interconnection locations and excitable system modes; a simulation module that models cyclic data center load behavior using a commercial positive sequence simulation platform; and an analysis module that computes risk metrics and generates interactive visualization dashboards. The risk metrics, formulated around simulation observables, map oscillation impacts to a three-stage severity scale spanning latent equipment fatigue through imminent cascading failure. The methodology is demonstrated on two Western Electricity Coordinating Council (WECC) system models: a publicly available 240-bus reduced representation and a detailed 2031 Heavy Winter planning case. Case studies illustrate that even modest 50 MW forced oscillations at resonant frequencies can produce wide-area power swings, N-1 security constraint violations, and cascading generator trips through protection actions - outcomes that would not occur under normal operating conditions without oscillations present. The results underscore the need for standardized oscillation impact assessment in large load interconnection studies and provide a reproducible, extensible framework for utilities to adopt or customize within their existing planning workflows.

Biswas, Shuchismita↗

DOE OSTI2022

Apparatus and method for high dynamic range counting by pixelated detectors

The present disclosure relates to an apparatus and methods for generating a hybrid image by high-dynamic-range counting. In an embodiment, the apparatus includes a processing circuitry configured to acquire an image from a pixelated detector, obtain a sparsity map of the acquired image, the sparsity map indicating low-flux regions of the acquired image and high-flux regions of the acquired image, generate a low-flux image and a high-flux image based on the sparsity map, perform event analysis of the acquired image based on the low-flux image and the high-flux image, the event analysis including detecting, within the low-flux image, incident events by an event counting mode, multiply, by a normalization constant, resulting intensities of the high-flux image and the detected incident events of the low-flux image, and generate the hybrid image by merging the low-flux image and the high-flux image.

Bammes, Benjamin↗

DOE OSTI2026

Terahertz 2D coherent spectroscopy for probing and controlling multicorrelations in quantum matter

Terahertz 2D coherent spectroscopy (THz-2DCS) is an emerging technique that brings multidimensional resolution to the ultrafast spectral–temporal dynamics of non-equilibrium quantum phases of matter, enabling new capabilities for precise coherent control in many-body dynamics and multiorder correlations. Here, by mapping and disentangling complex excitation and detection pathways across distinct time and frequency dimensions, THz-2DCS provides a form of coherence tomography of light-induced quantum matter — revealing multiquantum coherences, separating nonlinear response functions and capturing collective modes and quantum kinetics on ultrafast THz timescales. This Perspective discusses the technical capabilities of THz-2DCS, provides a comparison to other multidimensional and coherent transient spectroscopies and looks ahead towards opportunities for advancing THz-2DCS instrumentation and experimental strategies towards new frontier discoveries.

Huang, Chuankun [Ames Laboratory (AMES), Ames, IA ↗

DOE OSTI2023

Mesoscopic two-point collective dynamics of glass-forming liquids

The collective density–density and hydrostatic pressure–pressure correlations of glass-forming liquids are spatiotemporally mapped out using molecular dynamics simulations. It is shown that the sharp rise of structural relaxation time below the Arrhenius temperature coincides with the emergence of slow, nonhydrodynamic collective dynamics on mesoscopic scales. The observed long-range, nonhydrodynamic mode is independent of wave numbers and closely coupled to the local structural dynamics. Below the Arrhenius temperature, it dominates the slow collective dynamics on length scales immediately beyond the first structural peak in contrast to the well-known behavior at high temperatures. Furthermore, these results highlight a key connection between the qualitative change in mesoscopic two-point collective dynamics and the dynamic crossover phenomenon.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Mitigating contamination in LSS surveys: a comparison of methods

ABSTRACT Future large-scale structure surveys will measure the locations and shapes of billions of galaxies. The precision of such catalogues will require meticulous treatment of systematic contamination of the observed fields. We compare several existing methods for removing such systematics from galaxy clustering measurements. We show how all the methods, including the popular pseudo-Cℓ Mode Projection and Template Subtraction methods, can be interpreted under a common regression framework and use this to suggest improved estimators. We show how methods designed to mitigate systematics in the power spectrum can be used to produce clean maps, which are necessary for cosmological analyses beyond the power spectrum, and we extend current methods to treat the next-order multiplicative contamination in observed maps and power spectra, which reduced power spectrum errors from $\Delta \chi ^2_{\rm C_\ell }\simeq 10$ to ≃ 1 in simulated analyses. Two new mitigation methods are proposed, which incorporate desirable features of current state-of-the-art methods while being simpler to implement. Investigating the performance of all the methods on a common set of simulated measurements from Year 5 of the Dark Energy Survey, we test their robustness to various analysis cases. Our proposed methods produce improved maps and power spectra when compared to current methods, while requiring almost no user tuning. We end with recommendations for systematics mitigation in future surveys, and note that the methods presented are generally applicable beyond the galaxy distribution to any field with spatial systematics.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

A theory of phonon-induced friction on molecular adsorbates

In this manuscript, we provide a general theory for how surface phonons couple to molecular adsorbates. Our theory maps the extended dynamics of a surface’s atomic vibrational motions to a generalized Langevin equation, and by doing so captures these dynamics in a single quantity: the non-Markovian friction. The different frequency components of this friction are the phonon modes of the surface slab weighted by their coupling to the adsorbate degrees of freedom. Using this formalism, we demonstrate that physisorbed species couple primarily to acoustic phonons while chemisorbed species couple to dispersionless local vibrations. We subsequently derive equations for phonon-adjusted reaction rates using transition state theory and demonstrate that these corrections improve agreement with experimental results for CO desorption rates from Pt(111).

Science & Technology - Other Topics↗

DOE OSTI2021

Quantum-enhanced sensing of displacements and electric fields with two-dimensional trapped-ion crystals

Fully controllable ultracold atomic systems are creating opportunities for quantum sensing, yet demonstrating a quantum advantage in useful applications by harnessing entanglement remains a challenging task. Here, we realize a many-body quantum-enhanced sensor to detect displacements and electric fields using a crystal of ~150 trapped ions. The center-of-mass vibrational mode of the crystal serves as a high- Q mechanical oscillator, and the collective electronic spin serves as the measurement device. By entangling the oscillator and collective spin and controlling the coherent dynamics via a many-body echo, a displacement is mapped into a spin rotation while avoiding quantum back-action and thermal noise. We achieve a sensitivity to displacements of 8.8 ± 0.4 decibels below the standard quantum limit and a sensitivity for measuring electric fields of 240 ± 10 nanovolts per meter in 1 second. Feasible improvements should enable the use of trapped ions in searches for dark matter.

Gilmore, Kevin A.↗

DOE OSTI2026

SILICON CARBIDE THERMOMETRY USING RAMAN SPECTROSCOPY ON IRRADIATED TRISO PARTICLES

Silicon carbide (SiC) passive thermometry has emerged as a promising post-irradiation examination (PIE) technique for estimating irradiation temperature near the end of irradiation. While dilatometry techniques have been traditionally used to analyze prismatic samples after irradiation, Raman spectroscopy has recently been shown to provide comparable results by analyzing Raman-active phonon modes. In this work, Raman spectroscopy has been applied to the SiC layer of cross-sectioned irradiation tristructural isotropic (TRISO) particles from the AGR-5/6/7 experiment to evaluate the feasibility of particle-scale passive thermometry. Two-dimensional Raman mapping was used to measure the position of the SiC longitudinal optical (LO) phonon, which was then converted to an apparent irradiation temperature using a previously established empirical correlation. Particles from AGR-5/6/7 Compacts 2-2-1 and 5-1-3 were selected as their calculated time-averaged, volume-averaged (TAVA) temperatures (828°C and 706°C, respectively) fall within the range of the sensitivity of the experimental approach. The use of SiC thermometry was anticipated to confirm or highlight potential deviations from calculated end-of-life TAVA temperature across compacts. Four particles from Compact 2-2-1 and two particles from Compact 5-1-3 were selected based on 110mAg inventory (either some measurable activity or below the minimum detection limit) which is commonly used as an indicator of in-pile temperature variation of particles within the same compact. Across every particle selected it was determined that the average LO peak position was located around 968 cm-1 to 969 cm-1. Using the previously determined empirical correlation, this corresponds to an irradiation temperature around 950°C to 966°C, which does not align with the reported TAVA temperature values. This discrepancy in apparent irradiation temperatures likely reflects a combination of uncertainties in the calculated particle temperatures and differences in irradiation history between the present specimens and those used to establish the empirical Raman calibration such as neutron flux (damage rate) and SiC microstructure (as fabricated and irradiated).

Vawdrey, Josh [ORNL]↗

DOE OSTI2022

Search for Lepton Flavor Violation in Two Body Muon and Pion Decay at Rest

The ability of the Mu2e experiment to probe, or discover beyond the Standard Model physics in direct Charged Lepton Flavor Violation $\mu^+$ and $\pi^+$ decay modes is estimated. These direct modes are searched for simultaneously with proposed Mu2e detector validation runs, and are complementary to the Mu2e main search goal, an indirect search for $\mu^- \to e^-$ conversion at the sensitivity level of $\sim 10^{-17}$. The $\mu^+$ validation run will operate at 50% nominal magnetic field and reduced proton beam intensity to less than 1/100th nominal, in order to observe the e+ spectrum from $\mu^+$ decay, at and below the Michel edge Ee . 53 MeV. The $\pi^+$ validation run, based on measuring the mono-energetic e+ emission in the decay $\pi^+ \to e+\nu$, at 76% of nominal magnetic field and reduced beam intensity less than 1/5th nominal. Both of these runs can be used to fix the momentum scale for the Mu2e conversion search. In addition the muon validation dataset can be used to correct for systematic errors in the detector response by mapping the well known to O(\u03B13) corrected theoretical Michel spectrum, to the observed spectrum. One direct search is for two-body Charged Lepton Flavor Violation $\mu^+ \to e^+X$ decay, where $X$ is a light new physics particle. This allows Mu2e to explore well motivated models including axion like particles with flavor violating couplings and massive $Z^0$ bosons with more sensitivity then present astrophysical and laboratory constraints. In two weeks of data-taking, Mu2e can achieve direct mode 90% confidence level branching ratio limits of $10^{-7}$ over the mass range $20 \le m_X \le 50$ MeV, improving the current experimental limit at $10^{-5}$ by two orders of magnitude. In the mass range $m_X \le 20$ MeV, assuming systematic error corrections can be made by correcting the Monte Carlo mapping, the achievable search sensitivity is found to be $2.3\times 10^{-7}$ for $m_X =0$, an order of magnitude improvement over the current best limit at $2.6\times 10^{-6}$, when assuming $V+A$ or isotropic coupling. The $\pi^+$ validation run, allows searching for $\pi^+ \to e^+N$ decay, where $N$ is a heavy neutral lepton such as a heavy sterile neutrino, in the mass region $20 \le m_N \le 65$ MeV. A branching ratio limit at 90% confidence level of $3\times 10^{-8}$ can be achieved in two weeks, an improvement of the current search sensitivity limit by an order of magnitude.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2026

ORCHA: A performance portability system for extreme heterogeneity

Heterogeneity is the prevalent trend in the rapidly evolving high-performance computing (HPC) landscape in both hardware and application software. The diversity in hardware platforms, currently comprising various accelerators and a future possibility of specializable chiplets, poses a significant challenge for scientific software developers aiming to harness optimal performance across different computing platforms while maintaining the quality of solutions when their applications are simultaneously growing more complex. Code synthesis and code generation can provide mechanisms to mitigate this challenge. We have developed a divide and conquer approach where different aspects of performance are handled by different stand-alone tools that are interfaced with the application through generated code. This portability system, ORCHA, enables users to configure and orchestrate their computations among available resources on a platform by specifying a high-level recipe, thereby permitting a many-to-many paradigm where each recipe results in a different variant of the application. The core design goal is to let users decide the application’s hardware mapping and orchestration by editing only the high-level recipe—without modifying the maintained source code or binding the application to a particular runtime system. Tools in ORCHA distribution are: CG-Kit for translating the recipe into an execution graph; Milhoja to execute the graph by orchestrating data and task movement among hardware resources; and Macroprocessor that enables users to define their own code-shorthand for higher composability and easier management of code variants. Additionally, the design of ORCHA permits tools to work in a plug-and-play mode where the application can build and run without CG-Kit and Milhoja, and either tool can be swapped out for other tools with similar capabilities by modifying the code generation portion of ORCHA. In this paper, we describe the design of ORCHA and the role that code-generation plays in isolating applications from tools. We demonstrate the breadth of configurations ORCHA enables with a case study in which an application configuration is realized on three distinct hardware mappings—a GPU-centric, a CPU/GPU balanced, and a CPU/GPU concurrent layouts by using different recipes.

Lee, Youngjun↗

DOE OSTI2021

The effects of free surfaces on deformation twinning in HCP metals

Deformation twinning is a predominant mode of plastic deformation for hexagonal close packed metals, like Mg and Ti. The heterogenous microstructure and the local stresses associated with twinning play a key role in their mechanical response and fracture. Surface analyses, like electron microscopy, are frequently employed to spatially map microstructure and micromechanical fields in order to study twinning behavior. However, these measurements are inherently influenced by the vicinity of the free surface. In this work, an elasto-visco-plastic fast-Fourier-transform (EVP-FFT) polycrystal modeling approach is employed to investigate the effects of free surfaces on twin development before and after loading. We compare calculated micromechanical fields on free surfaces with those calculated inside the bulk and, in some cases, experimental surface measurements. The results indicate that the creation of free surfaces can promote twin propagation and growth and can influence twin morphology by causing a twin lamella to become larger, more blunted and irregular. The structure along the twin boundaries are also affected, due to the higher driving stresses that extend prismatic-basal and basal-prismatic facets. Furthermore, free surfaces invoke different slip activities in the twin and the surrounding parent crystal by enhancing basal, prismatic and pyramidal slip in some localized regions, while reducing slip in others. We demonstrate that the simulated free-surface effects lead to better qualitative and quantitative agreement with experimental measurements from scanning electron microscopy and digital image correlation.

36 MATERIALS SCIENCE↗