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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A Holistic Approach for Elucidating Local Structure, Dynamics, and Speciation in Molten Salts with High Structural Disorder

To examine ion solvation, exchange, and speciation for minority components in molten salts (MS) typically found as corrosion products, we propose a multimodal approach combining extended X-ray absorption fine structure (EXAFS) spectroscopy, optical spectroscopy, ab initio molecular dynamics (AIMD) simulations, and rate theory of ion exchange. Going beyond conventional EXAFS analysis, our method can accurately quantify populations of different coordination states of ions with highly disordered coordination environments via linear combination fitting of the EXAFS spectra of these coordination states computed from AIMD to the experimental EXAFS spectrum. In a case study of dilute Ni(II) dissolved in the ZnCl 2 +KCl melts, our method reveals heterogeneous distributions of coordination states of Ni(II) that are sensitive to variations in temperature and melt composition. These results are fully explained by the difference in the chloride exchange dynamics at varied temperatures and melt compositions. Finally, this insight will enable a better understanding and control of ion solubility and transport in MS.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Improved natural convection heat transfer correlations for reactor cavity cooling systems of high-temperature gas-cooled reactors: From computational fluid dynamics to Pronghorn

The Reactor Cavity Cooling System (RCCS) is a common reactor safety system in High Temperature Gas Cooled Reactors (HTGR) that removes heat from the Reactor Pressure Vessel (RPV) by radiation ($\sim 80\%$) and natural convection ($\sim 20\%$). For simulation of accident scenarios of HTGRs, intermediate fidelity and system codes models must be employed for limiting the models' execution time. While accurate quantification of the radiative heat transfer is available in these models, quantification of natural convection must rely on correlations of questionable accuracy for the Nusselt number. Commonly used correlations are based in experiments performed at low Rayleigh numbers and/or using isothermal walls in simplified geometries. Here, this work improves on the accuracy of natural convection heat transfer correlations in support for HTGR designs. These correlations include both local and average Nusselt numbers as a function of the global Rayleigh number, the local Rayleigh number, and the temperature profile at the hot wall of the RCCS. In the absence of dedicated experiments and the difficulty of performing high-fidelity simulations at realistic Rayleigh numbers, the data to fit the correlations are generated with Computational Fluid Dynamics (CFD) using Reynolds Averaged Navier-Stokes (RANS) models. First, a careful selection of the RANS turbulence model is performed by comparing the results obtained with different RANS turbulence models against high fidelity simulations of natural convection at $Ra \ 1 \times 10^{11}$ in a rectangular cavity. Next, the selected model is used to perform simulations of an HTGR cavity at different high Rayleigh numbers $\in [6.1 \times 10^{11},2.9 \times 10^{13}]$ to encompass several HTGR designs, assuming an isothermal RPV wall. The results obtained are used to fit a correlation for the average and space-varying Nusselt number as a function of the global and local Rayleigh numbers via a sparsity-promoting least-squares method. The selected RANS model is then used to perform simulations of a PBMR 400 HTGR cavity with the temperature profiles at the RPV wall obtained during a PLOFC transient. We use the results obtained to fit a temperature-dependent correction to the space-varying Nusselt number with the sparsity-promoting least-squares method. The results obtained in this work, enable system-level codes, such as Pronghorn, to perform higher-fidelity simulations of the heat exchange process in the RCCS while still maintaining a low computational cost.

42 ENGINEERING↗
DOE OSTI2023

Dynamic Modeling of a Solar-To-Hydrogen Flexible High Temperature Steam Electrolysis Plant

Sustainble hydrogen production for use as a renewable combustible fuel and clean chemical feedstock is an important objective as the world moves towards a renewable energy future. High temperature steam electrolysis is a promising hydrogen production technology due to its reduced electric input that is offset by heat input into steam generation and steam superheating. An option to provide this heat is to use concentrating solar thermal technology that can sustainably provide heat input while renewable electricity is used for the electrolysis reaction. In this work, a solar-to-hydrogen high temperature steam electrolysis plant is designed and dynamically modeled, showing continuous hydrogen production by utilizing supplemental heating and efficient recuperative heating from the electrolysis product streams. Through this design, over 90% of the required heat input for the process can by met by a combination of solar and recuperative heat. Additionally, the plant can flexibility operate by ramping down hydrogen production and through flexible heat integration, which intelligently integrates solar heat based on solar conditions. Smooth operation with flexible hydrogen production is demonstrated which decreases electrical input during on-peak grid times and also decreases the total supplemental heat load over the course of a day from 26.1% to 24.5%. In addition, by using flexible heat integration, the plant can increase its solar heat usage by 4.1% relative to a base case. Both options for flexibility show efficient use of solar thermal energy to sustainably and continuously produce hydrogen.

Immonen, Jake (ORCID:0000000341231625)↗
DOE OSTI2024

Phase transition kinetics revealed by in situ x-ray diffraction in laser-heated dynamic diamond anvil cells

We report successful coupling of dynamic loading in a diamond anvil cell and stable laser heating, which enables compression rates up to 500 GPa/s along high-temperature isotherms. Dynamic loading in a diamond-anvil cell allows exploration of a wider range of pathways in the pressure-temperature space compared to conventional dynamic compression techniques. By x-ray diffraction, we are able to characterize and monitor the structural transitions with the appropriate time resolution i.e., millisecond timescales. Using this method, we investigate the γ − ε phase transition of iron under dynamic compression, reaching compression rates of hundreds of GPa/s and temperatures of 2000 K. Our results demonstrate a distinct response of the γ − ε and α − ε transitions to the high compression rates achieved, possibly due to the different transition mechanisms. These findings open up new avenues to study tailored dynamic compression pathways in the pressure-temperature space and highlight the potential of this platform to capture kinetic effects (over ms time scales) in a diamond anvil cell. Published by the American Physical Society 2024

Ricks, Matthew (ORCID:000000015315612X)↗
DOE OSTI2021

Guest Editorial: Special Issue on recent advancements in electric power system planning with high-penetration of renewable energy resources and dynamic loads

The goal of this Special Issue is to present the state-of-the-art methodologies developed for expansion planning of all segments of the modern power systems, characterized by separated businesses, high penetration of renewable resources and new load types, as well as by application of technologically advanced solutions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Lasing dynamics of diode-pumped Yb – Er laser with a passive Q switch exposed to high-power external light

The temporal dynamics of diode-side-pumped Yb – Er laser, with a passive Co{sup 2+} : MgAl{sub 2}O{sub 4} Q switch illuminated by a light beam (total fluence of 0.15 – 0.16 J cm{sup −2}) from a semiconductor pulsed module, is investigated. It is shown that, using this external illumination, one can change the lasing onset delay and the time jitter ΔT{sub gi}. The dependence of ΔT{sub gi} on the interval between the instant of switching the illumination module on and the lasing peak position t{sub i} has a minimum at |t{sub i}| ≈ 10 μs. The decrease in ΔT{sub gi} with a change in |t{sub i}| from 90 to 10 μs indicates that instant of lasing peak occurrence for the Yb – Er laser is partially controlled by the pulse from the highly stable semiconductor module. If |t{sub i}| < 10 μs, the enhanced luminescence fluence in the cavity of Yb – Er laser exceeds 0.16 J cm{sup −2}; the light beam from the module does not affect much the lasing process in the ytterbium – erbium laser; and, as a consequence, the time jitter recovers the initial value. (paper)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Evaluation of a novel mid-infrared pyrometer for dynamic material experiments

Dynamic experiments create high-pressure shock waves on the microsecond time scale (or smaller), compressing materials to high pressures and temperatures and enabling the study of material properties at these conditions. Other dynamic studies use quasi-isentropic compression to produce similar high pressures at much lower temperatures. High pressure experiments performed on dynamic platforms such as gas-guns, laser, and pinch machines generate up to several hundred GPa in the sample pressure conditions12. Related static studies include diamond anvil cells, which obtain high pressures and have extremely high precision, but are most often conducted at room temperature or modest temperature increases (often <2000K). By combining these methods, material properties across a wide range of thermodynamic conditions can be probed, and a high quality equation of state (EOS) constructed.

36 MATERIALS SCIENCE↗
DOE OSTI2023

RNA structures and dynamics with Å resolution revealed by x-ray free-electron lasers

RNA macromolecules, like proteins, fold to assume shapes that are intimately connected to their broadly recognized biological functions; however, because of their high charge and dynamic nature, RNA structures are far more challenging to determine. We introduce an approach that exploits the high brilliance of x-ray free-electron laser sources to reveal the formation and ready identification of angstrom-scale features in structured and unstructured RNAs. Previously unrecognized structural signatures of RNA secondary and tertiary structures are identified through wide-angle solution scattering experiments. With millisecond time resolution, we observe an RNA fold from a dynamically varying single strand through a base-paired intermediate to assume a triple-helix conformation. While the backbone orchestrates the folding, the final structure is locked in by base stacking. This method may help to rapidly characterize and identify structural elements in nucleic acids in both equilibrium and time-resolved experiments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Performance evaluation of underground thermal storage integrated dual-source heat pump systems

The increasing demand for electricity stresses the existing electric grids. Buildings consume 73% of all U.S. electricity and are responsible for 30% of U.S. greenhouse gas emissions. Integrating thermal energy storage (TES) in building heating/cooling systems, which consume considerable electricity, can mitigate the challenges to electric grids. Here, this study reports on a novel thermal energy storage device integrated heat pump system to reshape the building electricity demand profile while maintaining thermal comfort. The annual performance of the proposed system has been evaluated through a dynamic system simulation with high fidelity in the Modelica platform. The dynamic model of the novel hybrid component named ‘dual purpose underground thermal battery’ was developed and validated. It was then incorporated into the system model. Given a time-of-use tariff, a rule-based control strategy was designed to shift the electric demand and switch the heat pump source for a typical single-family house in different climate zones of the United States. The system performance of the new TES-integrated dual-source heat pump was compared with that of a conventional air-source heat pump system. The results indicate that the proposed system can reduce the annual HVAC electricity cost by up to 52% while saving 45.2% on electricity consumption. In the Northern areas, the annual peak load of the HVAC system can be reduced by 64.9%. However, this reduction is less in the Southern areas as the system’s higher efficiency in winter dominates the overall energy-saving potential.

25 ENERGY STORAGE↗
DOE OSTI2021

pnnl/mol_dgnn

Molecular dynamics simulations often rely on parameterized atomistic potentials, which can be inaccurate compared to ab initio simulation methods. However, dynamic ab initio simulations come with high computational cost. Deep learning techniques offer a method to obtain both high accuracy and low cost predictions of dynamics. Our method gives a prediction of the structural dynamics of a molecule accounting for the prior dynamics, giving high-accuracy predictions at low computational cost

Ashby, Michael↗
DOE OSTI2020

Investigation of Superluminescent Diodes for Smart Lighting Systems. Final Report

The solid-state lighting ecosystem has evolved very rapidly over the last few years, with significant improvements in the technical performance of light-emitting diodes (LEDs) and the commoditization of LED-based lighting fixtures. As the performance of conventional lighting products begins to saturate, there is growing market interest in “Lighting as a Service” applications that will leverage advanced systems to impart new functionalities to lighting and improve energy efficiency, human health, and productivity. These “Smart Lighting” systems will include high-performance light sources, specialized sensors, and dynamic controls to deliver high quality, energy efficient, color tunable lighting with customized spatial light delivery and integrated visible light communication capability. To achieve these capabilities, smart lighting systems will place greater demands on the performance of light sources. Highly efficient sources with additional functionalities compared to conventional LEDs, such as small form factor, large modulation bandwidth, and spatially coherent output beams, will be required. While laser diodes have been proposed as potential sources for smart lighting systems, they also exhibit several properties that pose challenges, such as temporal coherence, extremely high spatial coherence, and ultra-narrow linewidths. To address these issues, we propose an investigation of an alternative device architecture known as a superluminescent diode (SLD). SLDs are similar in form to ridge laser diodes and share many of the same characteristics, such as stimulated emission operation, spatially coherent output, small form factor, and the potential for large modulation bandwidth. However, the operating principle for SLDs is distinct from laser diodes in that SLDs lack a strong cavity feedback mechanism, resulting in spatially coherent but temporally incoherent light output. Thus, SLDs may address the issues with laser diodes for lighting, while simultaneously maintaining some of the desirable characteristics of both laser diodes and LEDs. The objectives of this proposal are to design, grow, and fabricate blue (450 nm) SLDs on polar c-plane and nonpolar m-plane free-standing GaN substrates, and to evaluate their potential as sources in smart lighting systems through basic device characterization and detailed investigations of their efficiency droop and modulation bandwidth. The primary scientific aims of this work are to understand the fundamental role of optical gain in the superluminescent (non-lasing) regime on efficiency droop and modulation bandwidth in III-nitride emitters and to understand the effects of higher optical gain on SLD performance by comparing polar c-plane and nonpolar m-plane SLDs. The University of New Mexico (UNM) will collaborate with Sandia National Laboratories (SNL) and the Center for Integrated Nanotechnologies to design, fabricate, grow, and characterize the SLDs. UNM will perform the design and epitaxial growth, while SNL will focus on the fabrication and device characterization. The novelty of the proposed work includes the first comprehensive theoretical and experimental investigations of efficiency droop and the first investigation of modulation bandwidth in GaN-based emitters operating in the superluminescent regime. Moreover, the comparison of c-plane and m-plane SLDs will enable the first analysis of the effects of higher optical gain on the device performance. The development of high-performance GaN-based SLDs may enable efficiency gains and improved functionality in next-generation smart lighting systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Novel Design and Fabrication of a High Frequency Transient Heat Flux Sensor for Use in an RDE

Rotating detonation engine (RDE) combustion systems have been a topic of interest in the pressure gain combustion community for their benefits over traditional gas turbine engine combustors. However, cooling requirements for these engines are significantly higher and less predictable than non-detonating engines. To understand the high-speed heat transfer dynamics inside an RDE, a novel, high-frequency heat flux gage is presented. This study aims to design a robust, single-sided sensor that can withstand the high temperature and harsh environment of an RDE for extended durations. Sensor bench testing is performed using a hot plate as a heat source, and the sensor response is compared to a finite-element analysis (FEA) model. The sensor response is then tested inside a water-cooled RDE and the wall heat flux is compared to calorimetry data.

rotating detonation engines↗
DOE OSTI2025

Novel Design and Fabrication of a High Frequency Transient Heat Flux Sensor for Use in an RDE

Rotating detonation engine (RDE) combustion systems have been a topic of interest in the pressure gain combustion community for their benefits over traditional gas turbine engine combustors. However, cooling requirements for these engines are significantly higher and less predictable than non-detonating engines. To understand the high-speed heat transfer dynamics inside an RDE, a novel, high-frequency heat flux gage is presented. This study aims to design a robust, single-sided sensor that can withstand the high temperature and harsh environment of an RDE for extended durations. Sensor bench testing is performed using a hot plate as a heat source, and the sensor response is compared to a finite-element analysis (FEA) model. The sensor response is then tested inside a water-cooled RDE and the wall heat flux is compared to calorimetry data.

rotating detonation engines↗
DOE OSTI2023

Machine Learning for Daily Forecasts of Arctic Sea Ice Motion: An Attribution Assessment of Model Predictive Skill

Physics-based simulations of Arctic sea ice are highly complex, involving transport between different phases, length scales, and time scales. Resultantly, numerical simulations of sea ice dynamics have a high computational cost and model uncertainty. We employ data-driven machine learning (ML) to make predictions of sea ice motion. The ML models are built to predict present-day sea ice velocity given present-day wind velocity and previous-day sea ice concentration and velocity. Models are trained using reanalysis winds and satellite-derived sea ice properties. We compare the predictions of three different models: persistence (PS), linear regression (LR), and a convolutional neural network (CNN). We quantify the spatiotemporal variability of the correlation between observations and the statistical model predictions. Additionally, we analyze model performance in comparison to variability in properties related to ice motion (wind velocity, ice velocity, ice concentration, distance from coast, bathymetric depth) to understand the processes related to decreases in model performance. Results indicate that a CNN makes skillful predictions of daily sea ice velocity with a correlation up to 0.81 between predicted and observed sea ice velocity, while the LR and PS implementations exhibit correlations of 0.78 and 0.69, respectively. The correlation varies spatially and seasonally: lower values occur in shallow coastal regions and during times of minimum sea ice extent. LR parameter analysis indicates that wind velocity plays the largest role in predicting sea ice velocity on 1-day time scales, particularly in the central Arctic. Regions where wind velocity has the largest LR parameter are regions where the CNN has higher predictive skill than the LR.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Experimental Set-up for the Study of Chemical Fractionation and Aerosol Dynamics

Experimental investigations of chemical fractionation/phase partition and aerosol dynamics in high-temperature environment were reviewed and discussed. Particle composition and size distribution are the key data for aerosol dynamics predictive model and simulation. However, there were no particle size distribution available from the previous works. Nucleation, condensation, and coagulation are three key physical processes driving the fractionation or phase partition thereby the aerosol dynamics. A new approach was proposed to experimentally observe fractionation/phase partition and provide data for validating the predictive model for aerosol dynamics in the simulation of bomb debris formation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Hierarchical Materials from High Information Content Macromolecular Building Blocks: Construction, Dynamic Interventions, and Prediction

Hierarchical materials that exhibit order over multiple length scales are ubiquitous in nature. Because hierarchy gives rise to unique properties and functions, many have sought inspiration from nature when designing and fabricating hierarchical matter. More and more, however, nature’s own high-information content building blocks, proteins, peptides, and peptidomimetics, are being coopted to build hierarchy because the information that determines structure, function, and interfacial interactions can be readily encoded in these versatile macromolecules. Here, we take stock of recent progress in the rational design and characterization of hierarchical materials produced from high-information content blocks with a focus on stimuli-responsive and “smart” architectures. We also review advances in the use of computational simulations and data-driven predictions to shed light on how the side chain chemistry and conformational flexibility of macromolecular blocks drive the emergence of order and the acquisition of hierarchy and also on how ionic, solvent, and surface effects influence the outcomes of assembly. Furthermore, continued progress in the above areas will ultimately usher in an era where an understanding of designed interactions, surface effects, and solution conditions can be harnessed to achieve predictive materials synthesis across scale and drive emergent phenomena in the self-assembly and reconfiguration of high-information content building blocks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Exploring Physics of Ferroelectric Domain Walls in Real Time: Deep Learning Enabled Scanning Probe Microscopy

The functionality of ferroelastic domain walls in ferroelectric materials is explored in real-time via the in situ implementation of computer vision algorithms in scanning probe microscopy (SPM) experiment. The robust deep convolutional neural network (DCNN) is implemented based on a deep residual learning framework (Res) and holistically nested edge detection (Hed), and ensembled to minimize the out-of-distribution drift effects. The DCNN is implemented for real-time operations on SPM, converting the data stream into the semantically segmented image of domain walls and the corresponding uncertainty. Further the pre-defined experimental workflows perform piezoresponse spectroscopy measurement on thus discovered domain walls, and alternating high- and low-polarization dynamic (out-of-plane) ferroelastic domain walls in a PbTiO 3 (PTO) thin film and high polarization dynamic (out-of-plane) at short ferroelastic walls (compared with long ferroelastic walls) in a lead zirconate titanate (PZT) thin film is reported. This work establishes the framework for real-time DCNN analysis of data streams in scanning probe and other microscopies and highlights the role of out-of-distribution effects and strategies to ameliorate them in real time analytics.

36 MATERIALS SCIENCE↗