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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 631 records · Page 35

Nanoscale Electronics and Mechanics

The opportunities presented by nanomaterials are exciting and broad, with revolutionary implications spanning energy technologies, electronics, computing, sensing capabilities and biomedical diagnostics. Deriving the ultimate benefit from these materials will require the controlled assembly of diverse nanoscale materials across multiple length scales to design and achieve new properties and functionality, in other words, nanomaterials integration.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Evaporation Induced Entrainment of Contaminants from Evaporating and Burning Liquids.

This interim report details model development, theory, and a literature review focusing on the evaporation induced entrainment (sub-boiling) of contaminated liquids. Entrainment from a variety of sources is the topic of DOE Handbook 3010, and this report deals more broadly with fire related airborne sources of contaminants in hazardous operations. Relatively few studies have examined sub-boiling behavior in the past, however, it can be a phenomenon that presents a fire related risk under hazardous operations. Molecular dynamics simulations are used to infer the gaseous evolution of coordinated complexes, and a model for a water/plutonium/nitrate system is deduced from the simulation results by evaluating the statistical trends of the results. Questions remain as to the chemical reactivity and longevity of entrained species. A generalized computer model capability and simple analytical model assumptions are developed for predicting the results of these and other (boiling and solid entrainment) scenarios. Verification related predictions using these models are illustrated.

36 MATERIALS SCIENCE↗

Atrial Model Development and Prototype Simulations; Final Report for CRADA No. TC02224.0

This project was a collaborative effort between Lawrence Livermore National Security, LLC as manager and operator of Lawrence Livermore National Laboratory (LLNL) and Amgen, Inc. ("Amgen"), to develop a capability to computationally evaluate the importance and roles of different ion channels in atrial fibrillation. The first phase of this collaboration was to implement the atrial model, run prototype simulations, and analyze the results. Two No-Cost Time Extension (NCTE) requests were executed for this project. The first NCTE was executed on April 1, 2016, and extended the CRADA project for an additional two months to allow enough time to complete the tasks and deliverables, due to a delay in the start of the project. A second NCTE was executed on June 28, 2016, extending the project by three months, through November 3, 2016, to allow enough time to complete the final tasks and deliverables as well as negotiate a CRADA extension. The actual duration of this project was fourteen months. Amgen was unable to obtain budget approval to extend the CRADA past November 3, 2016. All of the deliverables for this CRADA project were successfully completed according to schedule.

59 BASIC BIOLOGICAL SCIENCES↗

Multiparametric optical label-free imaging to analyze plant cell wall assembly and metabolism. (Final Report)

Plant tissues are often considered not ideal for fluorescence imaging because of the pervasive intrinsic fluorescence of many plant metabolites and the intricate interactions with light of the many semi-crystalline polymers at the cell wall. Our project aims to take advantage of this observed shortcoming by developing a label-free, optical microscopy platform for characterizing multiple fingerprints of important cell wall components and stress-related, at subcellular scale resolution. The new imaging system can collect fingerprints from both emitted and scattered light that can inform on the chemical nature, subcellular distribution, anisotropy, and molecular environment of multiple cell wall components in intact plant tissues. We are combining these imaging capabilities with computational tools that enable correlated registration, integration, and analysis. This fully integrated, multiparametric optical system will be used to address biological problems connected to cell wall assembly in grasses. This includes a focus on developmental and environmental variation of cell wall impregnation with silica, lignin, suberin, and cutin in different tissues and cell types. Our research plan comprises three main goals: (1) To develop an accessible imaging platform and associated open-source software able to extract and integrate fingerprints from fluorescence-associated (multispectral emission, lifetime, and polarization), wide-field polarimetry, second harmonic generation (SHG), and stimulated Raman scattering signals (SRS); (2) To determine unique combination of fingerprints for various cell wall components and selected metabolites; (3) To analyze the process of cell wall silicification in grasses and determine how silicification affects cell wall properties and lignin, cutin, and suberin deposition in other cell types under differ stress conditions.

59 BASIC BIOLOGICAL SCIENCES↗

Adjoint Waveform Tomography for Next Generation Seismic Analyses and Monitoring

The development of methods and capabilities to compute complete waveform simulations in three-dimensional (3D) Earth models along with adjoint methods for computing the fully 3D sensitivity kernels in the 2000's set the stage for new advances in seismic imaging. I believe that the full benefits of adjoint waveform tomography (AWT) are not yet fully realized and this will be an important direction for the future of seismic tomography.

58 GEOSCIENCES↗

Building research capacity in Southern Appalachian mountain wetlands

This project increased research capacity in Southern Appalachian wetlands by facilitating new collaborations between the PI (UNC Asheville) and DOE and academic research partners. Mountain wetlands are among the rarest natural communities in the Southern Appalachians; most of the sites contain rare or endangered species and have been incorporated into or are being considered for the new Mountain Bogs National Wildlife Refuge (established in 2015). PI Wilcox’s research since 2010 has focused on wetland hydrology at over a dozen priority field sites in western North Carolina, eastern Tennessee, and northern Georgia. This project provided time and funding to learn about DOE programs and resources, including meteorological data, watershed modeling programs, analytical capabilities, and computing facilities. PI Wilcox was able to meet potential research partners at professional conferences and the DOE-BER-ESS PI meeting and invite several of those potential partners to visit UNC Asheville and nearby field sites in Western North Carolina. These connections have resulted in three new collaborative research proposals, and a new cooperative agreement with the US Fish and Wildlife Service that includes two new field sites.

54 ENVIRONMENTAL SCIENCES↗

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↗

Establishment of a Vertically Integrated Domestic Manufacturing Process for Production of Substrates Needed for Manufacture of Gas Diffusion Layers

In this project, AvCarb, LLC evaluated the baseline performance metrics of commercial carbon veils and their corresponding Gas Diffusion Layers (GDLs) with the goal of establishing an optimized, vertically integrated production system for wet-laid nonwoven substrates used in gas diffusion media for electrochemical energy storage and conversion devices. Mechanical testing and microstructural characterization were conducted and used to develop a multiscale computational model capable of simulating and predicting the performance of GDLs in fuel cells. Although the project successfully generated foundational transport and modeling data, it was terminated prior to identifying the critical GDL design parameters necessary for full optimization. The program aimed to improve carbon veil fabrication through enhanced fiber dispersion, fiber-fiber adhesion control, and improved web formation, enabling the production of high-quality, uniform substrates. Simulations were intended to guide mixing and solution delivery system design and process conditions, followed by production-scale trials to evaluate fiber dispersion, web uniformity, and mechanical robustness. At full deployment, the proposed production line would have been capable of producing approximately 650,000 m² of carbon veil annually. This capability remains strategically important, as the United States currently lacks a domestic source of wet-laid nonwoven carbon substrates that satisfy the stringent quality requirements for fuel-cell GDLs and electrolyzers representing an ongoing supply-chain vulnerability. Beyond supply-chain benefits, the project established a robust benchmarking dataset for existing commercial carbon veils while advancing next-generation material concepts targeting improved performance and manufacturing consistency.

Olson, Cynthia Lemay↗

Inverse Load Calculation of Wind Turbine Support Structures - A Numerical Verification Using the Comprehensive Simulation Code FAST: Preprint (Revised)

Physically measuring the dynamic responses of wind turbine support structures enables the calculation of the applied loads using an inverse procedure. In this process, inverse means deriving the inputs/forces from the outputs/responses. This paper presents results of a numerical verification of such an inverse load calculation. For this verification, the comprehensive simulation code FAST is used. FAST accounts for the coupled dynamics of wind inflow, aerodynamics, elasticity and turbine controls. Simulations are run using a 5-MW onshore wind turbine model with a tubular tower. Both the applied loads due to the instantaneous wind field and the resulting system responses are known from the simulations. Using the system responses as inputs to the inverse calculation, the applied loads arecalculated, which in this case are the rotor thrust forces. These forces are compared to the rotor thrust forces known from the FAST simulations. The results of these comparisons are presented to assess the accuracy of the inverse calculation. To study the influences of turbine controls, load cases in normal operation between cut-in and rated wind speed, near rated wind speed and between ratedand cut-out wind speed are chosen. The presented study shows that the inverse load calculation is capable of computing very good estimates of the rotor thrust. The accuracy of the inverse calculation does not depend on the control activity of the wind turbine.

17 WIND ENERGY↗

Reduced Models for Chemical Kinetics derived from Parallel Ensemble Simulations of Stirred Reactors

Detailed chemical kinetic models are essential to improve the predictive capability of computational fluid dynamics (CFD) simulations and to impact the development of next generation combustion technologies. However, such detailed kinetic models are beyond the reach of CFD codes due to the computational cost of transporting additional chemical degrees of freedom. Reduced order models for combustion kinetics exploit the presence of lower dimensional manifolds in the state space and require far fewer number of scalars to be transported as part of CFD simulations. In this paper, we describe the software infrastructure developed to allow large ensembles of stirred reactor configurations with detailed chemical kinetics. The canonical reactor simulations are incorporated in a workflow with sparse grid and data reduction methodologies aimed at development of reduced order models. We present results from analyzing the results of the stirred reactor calculations for syngas mixture using principal component analysis (PCA) and neural network methodologies. The results show that nonlinear autoencoder model can surpass PCA in representing the original dataset with far fewer degrees of freedom.

Zhang, Pei↗

Numerical Simulations of Combustion Instabilities in a Combustor with an Augmentor-Like Geometry

With the goal of assessing the capability of Computational Fluid Dynamics (CFD) to simulate combustion instabilities, the present work considers a premixed, bluff-body-stabilized combustor with well-defined inlet and outlet boundary conditions. The present simulations produce flow behaviors in good qualitative agreement with experimental observations. Notably, the flame flapping and standing acoustic waves seen in the experiments are reproduced by the simulations. Moreover, present predictions for the dominant instability frequency have an error of 7% and those of the rmspressure fluctuations show an error of 16%. In addition, an analysis of simulation results for the limit cycle complements previous experimental analyses by supporting the presence of an active frequency-locking mechanism.

Gonzalez-Juez, Esteban↗

MMMnet: A Neural Network Surrogate for Real-Time Transport Prediction Based on the Updated Multi-Mode Model

The Multi-Mode Model (MMM) is a physics-based anomalous transport model integrated into TRANSP for predicting electron and ion thermal transport, electron and impurity particle transport, and toroidal and poloidal momentum transport. While MMM provides valuable predictive capabilities, its computational cost, although manageable for standard simulations, is too high for real-time control applications. MMMnet, a neural network-based surrogate model, is developed to address this challenge by significantly reducing computation time while maintaining high accuracy. Trained on TRANSP simulations of DIII-D discharges, MMMnet incorporates an updated version of MMM (9.0.10) with enhanced physics, including isotopic effects, plasma shaping via effective magnetic shear, unified correlation lengths for ion-scale modes, and a new physics-based model for the electromagnetic electron temperature gradient mode. A key advancement is MMMnet’s ability to predict all six transport coefficients, providing a comprehensive representation of plasma transport dynamics. MMMnet achieves a two-order-of-magnitude speed improvement while maintaining strong correlation with MMM diffusivities, making it well-suited for real-time tokamak control and scenario optimization.

DIII-D↗

A framework to combine low- and high-resolution spectroscopy for the atmospheres of transiting exoplanets

Current observations of the atmospheres of close-in exoplanets are predominantly obtained with two techniques: low-resolution spectroscopy with space telescopes and high-resolution spectroscopy from the ground. Although the observables delivered by the two methods are in principle highly complementary, no attempt has ever been made to combine them, perhaps due to the different modeling approaches that are typically used in their interpretation. Here, we present the first combined analysis of previously published dayside spectra of the exoplanet HD 209458 b obtained at low resolution with HST/Wide Field Camera 3 (WFC3) and Spitzer/IRAC and at high resolution with VLT/CRIRES. By utilizing a novel retrieval algorithm capable of computing the joint probability distribution of low- and high-resolution spectra, we obtain tight constraints on the chemical composition of the planet’s atmosphere. In contrast to the WFC3 data, we do not confidently detect H{sub 2}O at high spectral resolution. The retrieved water abundance from the combined analysis deviates by 1.9σ from the expectations for a solar-composition atmosphere in chemical equilibrium. Measured relative molecular abundances of CO and H{sub 2}O strongly favor an oxygen-rich atmosphere (C/O < 1 at 3.5σ) for the planet when compared to equilibrium calculations including O rainout. From the abundances of the seven molecular species included in this study we constrain the planet metallicity to 0.1–1.0× the stellar value (1σ). This study opens the way to coordinated exoplanet surveys between the flagship ground- and space-based facilities, which ultimately will be crucial for characterizing potentially habitable planets.

79 ASTRONOMY AND ASTROPHYSICS↗

Roadmap for warm dense matter physics

This roadmap presents the state-of-the-art, current challenges and near future developments anticipated in the thriving field of warm dense matter physics. Originating from strongly coupled plasma physics, high pressure physics and high energy density science, the warm dense matter physics community has recently taken a giant leap forward. This is due to spectacular developments in laser technology, diagnostic capabilities, and computer simulation techniques. Only in the last decade has it become possible to perform accurate enough simulations \& experiments to truly verify theoretical results as well as to reliably design experiments based on predictions. Consequently, this roadmap discusses recent developments and contemporary challenges that are faced by theoretical methods, and experimental techniques needed to create and diagnose warm dense matter. A large part of this roadmap is dedicated to specific warm dense matter systems and applications in astrophysics, inertial confinement fusion and novel material synthesis.

FOS: Physical sciences↗

Hybrid Monte Carlo/Deterministic Methods for Accelerating Active Interrogation Modeling

The potential for smuggling special nuclear material (SNM) into the United States is a major concern to homeland security, so federal agencies are investigating a variety of preventive measures, including detection and interdiction of SNM during transport. One approach for SNM detection, called active interrogation, uses a radiation source, such as a beam of neutrons or photons, to scan cargo containers and detect the products of induced fissions. In realistic cargo transport scenarios, the process of inducing and detecting fissions in SNM is difficult due to the presence of various and potentially thick materials between the radiation source and the SNM, and the practical limitations on radiation source strength and detection capabilities. Therefore, computer simulations are being used, along with experimental measurements, in efforts to design effective active interrogation detection systems. The computer simulations mostly consist of simulating radiation transport from the source to the detector region(s). Although the Monte Carlo method is predominantly used for these simulations, difficulties persist related to calculating statistically meaningful detector responses in practical computing times, thereby limiting their usefulness for design and evaluation of practical active interrogation systems. In previous work, the benefits of hybrid methods that use the results of approximate deterministic transport calculations to accelerate high-fidelity Monte Carlo simulations have been demonstrated for source-detector type problems. In this work, the hybrid methods are applied and evaluated for three example active interrogation problems. Additionally, a new approach is presented that uses multiple goal-based importance functions depending on a particle s relevance to the ultimate goal of the simulation. Results from the examples demonstrate that the application of hybrid methods to active interrogation problems dramatically increases their calculational efficiency.

active interrogation↗

ALARM STRATEGY AND COMPLEXITY: PREDICTIONS OF OPERATOR RESPONSE

Decision support for operators is not new, and much has been written regarding the potential usefulness of digital support systems and alarm filtering strategies. However, determining the appropriate characteristics of decision support tools is difficult, especially when alarms can vary in the manner which diagnostic information is formulated and displayed and when event scenario types are complex and numerous. When first reviewed, the advantages or disadvantages of a particular alarm approach may not be apparent to the designer or analyst. The present research focuses on the review of two particular alarm strategies, binary alarm type (BAT) and likelihood alarm type (LAT), and reviews their influence upon accuracy, bias, and trust for tasks performed at a computer workstation capable of replicating a series of control-room-like alarms. The findings are discussed in terms of the of the performance advantages of likelihood alarm technology and related research as an aid to the alarm design process.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

HAWC2 and BeamDyn: Comparison Between Beam Structural Models for Aero-Servo-Elastic Frameworks: Preprint

This work presents a comparison of two beam codes for aero-servo-elastic frameworks: a new structural model for the aeroelastic code HAWC2 and a new nonlinear beam model, BeamDyn, for the aeroelastic modularization framework FAST v8. The main goal is to establish the suitability of the two approaches to model the structural behaviour of modern wind turbine blades in operation. Through a series of benchmarking structural cases of increasing complexity, the capability of the two codes to simulate highly nonlinear effects is investigated and analyzed. Results show that even though the geometrically exact beam theory can better model effects such as very large deflections, rotations, and structural couplings, an approach based on a multi-body formulation assembled through linear elements is capable of computing accurate solutions for typical nonlinear beam theory benchmarking cases.

17 WIND ENERGY↗

HAWC2 and BeamDyn: Comparison Between Beam Structural Models for Aero-Servo-Elastic Frameworks

This work presents a comparison of two beam codes for aero-servo-elastic frameworks: a new structural model for the aeroelastic code HAWC2 and a new nonlinear beam model, BeamDyn, for the aeroelastic modularization framework FAST v8. The main goal is to establish the suitability of the two approaches to model the structural behaviour of modern wind turbine blades in operation. Through a series of benchmarking structural cases of increasing complexity, the capability of the two codes to simulate highly nonlinear effects is investigated and analyzed. Results show that even though the geometrically exact beam theory can better model effects such as very large deflections, rotations, and structural couplings, an approach based on a multi-body formulation assembled through linear elements is capable of computing accurate solutions for typical nonlinear beam theory benchmarking cases.

17 WIND ENERGY↗