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At least 1,261 records · Page 70

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DOE OSTI2020

Machine learning enabled lineshape analysis in optical two-dimensional coherent spectroscopy

Optical two-dimensional (2D) coherent spectroscopy excels in studying coupling and dynamics in complex systems. The dynamical information can be learned from lineshape analysis to extract the corresponding linewidth. However, it is usually challenging to fit a 2D spectrum, especially when the homogeneous and inhomogeneous linewidths are comparable. We implemented a machine learning algorithm to analyze 2D spectra to retrieve homogeneous and inhomogeneous linewidths. The algorithm was trained using simulated 2D spectra with known linewidth values. The trained algorithm can analyze both simulated (not used in training) and experimental spectra to extract the homogeneous and inhomogeneous linewidths. Finally, this approach can be potentially applied to 2D spectra with more sophisticated spectral features.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2021

TEAMER - AquaHarmonics High Fidelity WEC Sim PTO and Control Model Validation, Sim Model

Collaborative effort between AquaHarmonics, Sandia National Laboratories (SNL), and the National Renewable Energy Laboratory (NREL) to revise and validate Aquaharmonics' full wave to wire model, allowing for reduced uncertainty and increased understanding of design requirements of a utility scale wave energy converter (WEC). SNL and NREL in collaboration with AquaHarmonics, will set up and run WEC Simulator (WEC-Sim) models of the AquaHarmonics WEC, building off past model developments for inclusion of custom PTO (power take-off) dynamics. The intent is to review, update, and verify or validate a new WEC-Sim model against wave tank experimental data. Furthermore, the WEC-Sim model will be coupled to an energy storage system model to better understand the wave-to-wire functionality. Project is part of the TEAMER (Testing & Expertise for Marine Energy) RFTS (request for technical support) system of WEC research projects. Testing data can be found in the associated MHKDR link below.

16 TIDAL AND WAVE POWER↗

DOE OSTI2021

TEAMER - AquaHarmonics High Fidelity WEC Sim PTO and Control Model Validation, Test Logs and Results

Collaborative effort between AquaHarmonics, Sandia National Laboratories (SNL), and the National Renewable Energy Laboratory (NREL) to revise and validate Aquaharmonics' full wave to wire model, allowing for reduced uncertainty and increased understanding of design requirements of a utility scale wave energy converter (WEC). SNL and NREL in collaboration with AquaHarmonics, will set up and run WEC Simulator (WEC-Sim) models of the AquaHarmonics WEC, building off past model developments for inclusion of custom PTO (power take-off) dynamics. The intent is to review, update, and verify or validate a new WEC-Sim model against wave tank experimental data. Furthermore, the WEC-Sim model will be coupled to an energy storage system model to better understand the wave-to-wire functionality. This data set is described in the "Test Log" excel file. Please refer to that document for details on each specific test date/time, constraint parameters and model hardware setup details. Sim model can be found in the associated MHKDR link below.

16 TIDAL AND WAVE POWER↗

DOE OSTI2025

Data for Machado-Silva et al. (2024), "Short-Term Groundwater Level Fluctuations Drive Subsurface Redox Variability"

This dataset contains the analytical data reported in Machado-Silva et al. (2024) as part of the COMPASS-FME project, which seeks to advance a scalable, predictive understanding of the fundamental biogeochemical processes, ecological structure, and ecosystem dynamics that distinguish coastal terrestrial-aquatic interfaces from the purely terrestrial or aquatic systems to which they are coupled. The dataset consists of water quality parameters as well as redox potential, water content, and electrical conductivity. These data were collected in 2022 in Crane Creek (CRC), Portage River (PTR), and Old Woman Creek (OWC). Each of these sites included uplands (UP), transitions (TR), wetland-transition edge (WTE), and wetland (W) zones. The sites represent replicates of the Lake Erie terrestrial-aquatic interface under fluctuating water levels and are located in well-preserved areas with natural or restored marsh and forest cover.This dataset consists of a single data file (Machado_Silva_et_al_2024_EST_data.csv) that is in comma-separated value (CSV) format. No special software is required to read it.This dataset uses the ESS-DIVE Hydrologic Monitoring Reporting Format 1.0.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Data for Stetten et al. (2025), "Biogeochemical controls on iron speciation and cycling across upland to shoreline gradients in freshwater and estuarine coastal soils (Lake Erie and Chesapeake Bay, United States)"

Coastal environments are dynamic interfaces that mediate carbon and nutrient exchanges between terrestrial landscapes and open waters, but it is unclear how biogeochemical reactions, in particular iron (Fe) redox transformations, affect the understanding and prediction of coastal ecosystem functions. This dataset includes measurements from two freshwater sites in the Western and Central basins of Lake Erie (Ohio, United States) and two estuarine sites in the Chesapeake Bay (Maryland, United States); the analytical results were reported by Stetten et al. (2025) in Science of the Total Environment. It was produced as part of the COMPASS-FME project, which seeks to advance a scalable, predictive understanding of the fundamental biogeochemical processes, ecological structure, and ecosystem dynamics that distinguish coastal terrestrial-aquatic interfaces from the purely terrestrial or aquatic systems to which they are coupled. The sites were sampled in November 2022 (CRC), December 2022 (MSM), February 2023 (GCW), and March 2023 (OWC); site codes follow those used by Pennington et al. (2025).The dataset consists of the following soil data:- Solid data (Fe concentration, etc.)- Porewater data (sulfate, sulfide, etc.)- Linear combination fitting results of X-ray absorption near edge structure (XANES) spectra; i.e., quantitative results of the oxidation state of Fe, indicated as a proportion of pure Fe(III) and Fe(II) model compounds- Linear combination fitting results of EXAFS (extended X-ray absorption fine structure) spectra, indicated as proportion of of Fe-model compounds (illite, smectite, etc.)Each data type has a single file in comma-separated value (CSV) format. No special software is required to read it.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Lattice phase shifts and mixing angles for an arbitrary number of coupled channels

We present a lattice method for determining scattering phase shifts and mixing angles for the case of an arbitrary number of coupled channels. The proposed method combines a spherical wall boundary condition and a channel-mixing auxiliary potential to extract the full-rank S-matrix from the radial wave functions. We consider the scattering problem of two spin-1 bosons interacting with a test potential involving up to four coupled channels. For this benchmark system, the phase shifts and mixing angles are shown to agree on the lattice and in the continuum. Our method should allow to extend previous two-channel nuclear lattice EFT simulations to mixing of more than two partial waves.

Bovermann, Lukas↗

DOE OSTI2020

Hot Electron Scaling and Energy Coupling In Nonlinear Laser Plasma Interactions

Energy conversion from high power lasers to energetic hot electrons is a fundamental phenomenon in laser-plasma interactions. At laser intensities above a few times 10 14 W/cm 2 , nonlinear laser-plasma interactions lead to the generation of hot electrons with a broad energy distribution at typical temperatures of 10’s – 100’s kilo-electron-volt (keV). The fraction of laser energy transferred to hot electrons, their energy distribution and energy coupling efficiency to the targets are strongly affected by the laser intensity, wavelength and the plasma condition. Most investigations to date that are related to the fusion of high-energy-density laboratory plasmas (HEDLP) are carried out with relatively moderate laser intensity and lower laser wavelength to minimize hot electron generation, as electron preheating can degrade the fuel assembly. An alternative fusion scheme known as shock ignition (SI) has been proposed, requiring a high intensity spike pulse at the end of a fuel assembly phase to generate a strong shock to ignite the fuel. An initial shock pressure of 0.3 Gbar is required for ignition-scale targets using the SI scheme, requiring a relatively high on-target laser intensity of 5-10X10 15 W/cm 2 for the spike pulse. At such intensities, copious hot electrons can be produced by laser-plasma-instabilities (LPI), e.g., Stimulated Raman Scattering (SRS) and Two-Plasmon Decay (TPD). While very energetic electrons (>200 keV) could preheat the fuel, electrons with moderate energies may actually be beneficial for the SI scheme. Electrons in the 50-100 keV range can be stopped in the compressed high-density outer ablator layer leading to an increase in the ignitor shock strength and therefore enhancing overall efficiency in the SI scheme. Considering this importance of total energy and temperature of hot electrons, it is necessary to understand the LPI in the SI high intensity regime. Characterizing the hot electron source and energy coupling is key to investigating the viability of the SI concept. The overall goal of the HEDLP award was to perform a detailed study of the scaling of hot electron generation and energy coupling on high power laser systems, with intensity, wavelength, and target ablator material relevant to the nonlinear laser-plasma interaction at SI relevant conditions. This was a collaborative project between the Center for Energy Research at the University of California, San Diego (UCSD) and General Atomics. The experiment was performed at the Omega Laser Facility at the Laboratory for Laser Energetics (LLE) in the University of Rochester. Specific objectives of the work were to: understand the basic physics of laser-plasma interactions and instabilities at high laser intensities (up to 10 17 W/cm 2 ) and the effects of low-Z ablator materials and laser wavelengths (IR pulse at 1.054 µm versus UV pulse at 0.351 µm) and intensity scaling, fully characterize the resultant hot electron energy distribution, validate hot electron energy deposition via collisional and kinetic processes in the target and the induced shocks in support of electron-assisted SI concept.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Code Demonstration: Approximation of nearly-periodic symplectic maps via structure-preserving neural networks

In this notebook, we use the symplectic gyroceptron architecture from [Duruisseaux et al., 2022] to learn a surrogate map for the nearly-periodic symplectic flow map associated to a nearly-periodic Hamiltonian system composed of two nonlinearly coupled oscillators, where one of them oscillates significantly faster than the other: $\Big\lbrace$ $ {\dot{q}_1 = p_1 \hspace{5mm} \dot{p}_1 = -q_1 - \epsilon \partial_{q1}U(q_1 , q_2 )} \atop {\dot{q}_2 = \epsilon p_2 \hspace{4mm} \dot{p}_2 = -\epsilon q_2 - \epsilon \partial_{q2}U(q_1 , q_2 )}$. These equations of motion are the Hamilton's equations associated to the Hamiltonian $H_{\epsilon}(q_1,q_2,p_1,p_2)=\frac{1}{2}(q^2_1+p^2_1)+\frac{1}{2}\epsilon(q^2_2+p^2_2)+\epsilon$$U(q_1,q_2)$.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Heterogeneous Polymer Dynamics Explored Using Static 1H NMR Spectra

NMR spectroscopy continues to provide important molecular level details of dynamics in different polymer materials, ranging from rubbers to highly crosslinked composites. It has been argued that thermoset polymers containing dynamic and chemical heterogeneities can be fully cured at temperatures well below the final glass transition temperature (Tg). In this paper, we described the use of static solid-state 1H NMR spectroscopy to measure the activation of different chain dynamics as a function of temperature. Near Tg, increasing polymer segmental chain fluctuations lead to dynamic averaging of the local homonuclear proton-proton (1H-1H) dipolar couplings, as reflected in the reduction of the NMR line shape second moment (M2) when motions are faster than the magnitude of the dipolar coupling. In general, for polymer systems, distributions in the dynamic correlation times are commonly expected. To help identify the limitations and pitfalls of M2 analyses, the impact of activation energy or, equivalently, correlation time distributions, on the analysis of 1H NMR M2 temperature variations is explored. It is shown by using normalized reference curves that the distributions in dynamic activation energies can be measured from the M2 temperature behavior. An example of the M2 analysis for a series of thermosetting polymers with systematically varied dynamic heterogeneity is presented and discussed.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Load-decoupling attachment system

A load-decoupling attachment system is configured to secure a component to a primary structure. The load-decoupling system includes a fore end coupling bracket that is configured to attach to a fore end of the component. A first tie rod is coupled to the fore end coupling bracket. The first tie rod is configured to couple to a first portion of the primary structure. A second tie rod is coupled to the fore end coupling bracket. The second tie rod configured to couple to a second portion of the primary structure. A universal joint mount assembly is configured to couple to an aft end of the component and a third portion of the primary structure.

Weathers, Jeffrey W.↗

DOE OSTI2021

Balanced light detector

A system and method with AC coupling that reserves photodiode bandwidth in a biased configuration, allows optimal transimpedance amplifier performance, retains DC signal measurement capability, and does not introduce noise into the balanced detection signal.

Williams, Brian P.↗

DOE OSTI2023

Balanced light detector

Williams, Brian P.↗

DOE OSTI2023

Resonator-based ion-selective sensor

The present disclosure relates to systems and methods suitable to measure trace amounts of specific ions in fluid samples. An example system includes a resonator having an input coupler and an output coupler. The example system also includes an ion-selective membrane (ISM) optically coupled to at least a portion of the resonator. The system additionally includes a light source configured to illuminate the resonator by way of the input coupler. Furthermore, the system includes a detector configured to receive output light by way of the output coupler and provide information indicative a concentration of a specific ion proximate to tire ISM.

Zhang, Xufeng↗

DOE OSTI2023

Runtime extension for neural network training with heterogeneous memory

Systems, apparatuses, and methods for managing buffers in a neural network implementation with heterogeneous memory are disclosed. A system includes a neural network coupled to a first memory and a second memory. The first memory is a relatively low-capacity, high-bandwidth memory while the second memory is a relatively high-capacity, low-bandwidth memory. During a forward propagation pass of the neural network, a run-time manager monitors the usage of the buffers for the various layers of the neural network. During a backward propagation pass of the neural network, the run-time manager determines how to move the buffers between the first and second memories based on the monitored buffer usage during the forward propagation pass. As a result, the run-time manager is able to reduce memory access latency for the layers of the neural network during the backward propagation pass.

Mappouras, Georgios↗

DOE OSTI2024

Multiphysics Time-Integration for Turbulent Combustion at the Exascale

Turbulent reacting flow systems are often modeled with coupled time-dependent partial differential equations (PDEs). Solving such equations can easily tax the world's largest supercomputers. One pragmatic strategy for attacking such problems is to split the PDEs into components that can more easily be solved in isolation. This generic operator-splitting strategy leads to a set of ordinary differential equations (ODEs) that need to be solved as part of an "outer-loop" time-stepping approach. In many combustion applications, the ODEs to be solved can be very stiff, exhibiting timescales that span many orders of magnitude. The SUNDIALS library provides a plethora of robust time integration algorithms for solving these ODEs on exascale-capable computing hardware, yet for many complex applications (such multicomponent fuels or emissions predictions), the chemical models remain too complex to solve using reasonable resources. The Quasi-Steady State Approximation (QSSA) can be an effective tool for reducing the size and stiffness of the simulations. In this talk, I will discuss the use of the SUDIALS library of ODE solvers together with automatic code generation tools to solve complex turbulent reacting flow problems using QSSA models.

chemistry↗

DOE OSTI2025

Undulating transducer for energy harnessing and propulsion apparatuses, methods and systems

Embodiments disclosed may serve the function of a pump, a generator, or a propulsion system. Two flexible fins are coupled via their longitudinal inner edges to fin coupling modules. An external fluid flow causes traveling fin undulations. The angle of the fins relative to each other changes as undulations travel along the fins which can be translated through the fin coupling modules into mechanical work, powered by the external fluid flow. The mechanical work of the fin coupling modules may be the cyclical extension and contraction of pistons or bellows incorporated into the fin coupling modules, which may draw ambient fluid during their extension cycles and compress fluid during their contraction cycles to create a pump. The pistons or bellows may also be sealed from ambient fluid but connected through conduits through which contained fluid is exchanged in a continuous circulation of fluid to power a pump or a turbine.

Filardo, Benjamin Pietro↗

DOE OSTI2025

AUTOMATIC GENERATION OF EVENT TREES AND FAULT TREES: A MODEL-BASED APPROACH

In the past few decades, increasing complexity in modern engineering systems has been driven by the integration of a large number of components and by the fact that the system operations involve many disciplines (e.g., thermal-hydraulics, plant operations, cyber-security). Current safety/reliability modeling approaches to such systems are labor intensive, difficult to learn, and rely heavily on simplistic Boolean logic to depict failure propagation and accident progression. While these methods serve well for simple systems (i.e., linear causal systems with limited small inter- and intra-system interactions), their results are difficult to verify when modeling complex systems (typically performed through the extensive use of modeling assumptions). The development of new methods is addressed to meet these challenges through a model-based system engineering (MBSE) lens. Under MBSE philosophy, every aspect of the system (form or function) is represented by a model that completely characterizes its architecture or behavior. MBSE approach greatly improves the management of design, analysis and verification of complex systems. An integration of Dynamic Probabilistic Risk Assessment (DPRA) methods with MBSE models is proposed to perform safety/reliability analyses of engineering systems. In particular, MBSE representation of the system (performed using Systems Modeling Language [SysML]) is coupled with DPRA methods to automatically generate event trees and fault trees.

97 - MATHEMATICS AND COMPUTING↗

DOE OSTI2025

A Model Based Approach to Extract Health Information from Textual Data

In current nuclear power plants (NPPs) a large amount of condition-based data is being generated and stored to assess and monitor component health and performance. The format of this data can be either numeric (e.g., pump vibration data) or textual (e.g., condition report which assess component health). While assessing component health from numeric data can be performed with a large variety of methods, the extraction of information from textual data still remains a challenge. Natural language processing (NLP) methods are starting to be deployed in current NPPs mainly to filter out incident reports (IRs) that are not safety related by employing supervised machine learning methods. However, these methods do not really provide the quantitative information that might be contained in IRs. This paper presents an approach to extract information from textual data (e.g., from IRs, maintenance reports) that is based on NLP data analytics methods coupled with model-based system engineer (MBSE) models. NLP methods are employed to perform syntactic and semantic analyses. Syntactic analysis analyzes the grammatical structure of a sentence; such analysis includes: part of speech (POS) tagging (i.e., identification of grammatic elements of each string - e.g., nouns, verbs), named entity recognition (i.e., identification of text entities - e.g., names, dates, events), and relation extraction (e.g., coreference resolution). On the other hand, semantic analysis is designed to analyze the logic structure of a sentence. Through a specific set of rules, our methods can identify whether a sentence contains health information of a component (e.g., degraded performance, anomaly behavior) or the causal relationship between two events (i.e., a cause-effect pair). An innovative element of our approach is that semantic analysis relies on MBSE models to identify links between textual elements. MBSE are diagrams designed to represent system and component dependencies (from both a form and functional point of view). In our approach, MBSE models emulate system engineer knowledge about component/system architecture. This paper presents in detail how the integration of NLP methods and MBSE models is performed. Few analysis examples focusing on centrifugal pumps are presented.

97 - MATHEMATICS AND COMPUTING↗