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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Reconfigurable structure and tunable transport in synchronized active spinner materials

Ensembles of actuated colloids are excellent model systems to explore emergent out-of-equilibrium structures, complex collective dynamics, and design rules for the next generation materials. Here, we demonstrate that ferromagnetic microparticles suspended at an air-water interface and energized by an external rotating magnetic field spontaneously form dynamic ensembles of synchronized spinners in a certain range of the excitation field parameters. Each spinner generates strong hydrodynamic flows, and collective interactions of the multiple spinners promote a formation of dynamic lattices. On the basis of experiments and simulations, we reveal structural transitions from liquid to nearly crystalline states in this novel active spinner material and demonstrate that dynamic spinner lattices are reconfigurable, capable of self-healing behavior and that the transport of embedded inert cargo particles can be remotely tuned by the parameters of the external excitation field. Our findings provide insights into the behavior of active spinner materials with reconfigurable structural order and tunable functionalities.

36 MATERIALS SCIENCE↗
DOE OSTI2019

High-Fidelity Simulation of Flow-Induced Vibrations in Helical Steam Generators for Small Modular Reactors

Flow-induced vibration (FIV) is a widespread problem in energy systems as they rely on fluid movement for energy conversion. Vibrating structures may be damaged as fatigue or wear occur. Given the importance of reliable components in the nuclear industry, FIV has long been a major concern in the safety and operation of nuclear reactors. In particular, nuclear fuel rods and steam generators have been known to suffer from FIV and related failures. In this paper we discuss the use of the computational fluid dynamics code Nek5000 coupled to the structural code Diablo to simulate the flow in helical coil heat exchangers and associated FIV. In particular, one-way coupled calculations are performed, where pressure and tractions data are loaded into the structural model. The main focus of this paper is on validation of this capability. Fluid-only Nek5000 large eddy simulations are first compared against dedicated high-resolution experiments. Then, one-way coupled calculations are performed with Nek5000 and Diablo for two data sets that provide FIV data for validation. These calculations were aimed at simulating available legacy FIV experiments in helical steam generators in the turbulent buffeting regime. In this regime one-way coupling is judged sufficient since the pressure loads do not cause substantial displacements. It is also the most common source of vibration in helical steam generators at the low flows expected in integral pressurized water reactors. We discuss validation of two-way coupled experiments and benchmarks toward the simulation of fluid elastic instability. We briefly discuss the application of these methods to grid-to-rod fretting.

Flow-Induced Vibration↗
DOE OSTI2019

Hydrodynamic and Structural Response Modeling of a Prototype Floating Membrane Reservoir System for Pumped Storage Hydropower

Hydrodynamic, computational fluid dynamics, and finite-element modeling were performed for a novel floating membrane reservoir system design for closed-loop pumped storage hydropower application. The conceptual design, which is now protected under an invention disclosure with a patent pending, offers a potential low-cost, low-impact solution to address the high costs, long investment return periods, and environmental disruptions encountered with traditional pumped storage development while offering modularity to enable replication at many locations. Prior to physical tests on a prototype, this paper documents the response analysis and modeling completed to simulate hydraulic and structural performance under different reservoir deployment and alignment arrangements, evaluate system stability, and refine the conceptual design. The results indicate that the excitation frequency from vortex shedding is at least an order of magnitude lower than the water sloshing frequencies in the reservoir, the structural natural frequency of the entire reservoir, and the vibrational frequencies of the side membranes, although excitation frequencies from other sources could cause mechanical resonance under certain conditions. To control destabilizing effects and prevent rocking motion and vibration, the authors conclude that the design could be improved by including a support structure around the floating reservoir, which could also provide floating-membrane containment, improve safety, and facilitate vertical reservoir movement. These conclusions, based on hydrodynamic and structural response modeling, help define specifications for upcoming full-scale prototype construction, deployment, and testing. This study demonstrates standard modeling technique application to an innovative design for which similar applications have not been previously evaluated. As a result, the refined design is capable of improving the scalability and feasibility of pumped storage hydropower in the United States and will be considered for commercialization following prototype testing.

13 HYDRO ENERGY↗
DOE OSTI2023

Social network structure and the spread of complex contagions from a population genetics perspective

Ideas, behaviors, and opinions spread through social networks. If the probability of spreading to a new individual is a non-linear function of the fraction of the individuals’ affected neighbors, such a spreading process becomes a “complex contagion”. This non-linearity does not typically appear with physically spreading infections, but instead can emerge when the concept that is spreading is subject to game theoretical considerations (e.g. for choices of strategy or behavior) or psychological effects such as social reinforcement and other forms of peer influence (e.g. for ideas, preferences, or opinions). Here we study how the stochastic dynamics of such complex contagions are affected by the underlying network structure. Motivated by simulations of complex contagions on real social networks, we present a framework for analyzing the statistics of contagions with arbitrary non-linear adoption probabilities based on the mathematical tools of population genetics. The central idea is to use an effective lower-dimensional diffusion process to approximate the statistics of the contagion. This leads to a tradeoff between the effects of ”selection” (microscopic tendencies for an idea to spread or die out), random drift, and network structure. Our framework illustrates intuitively several key properties of complex contagions: stronger community structure and network sparsity can significantly enhance the spread, while broad degree distributions dampen the effect of selection compared to random drift. Finally, we show that some structural features can exhibit critical values that demarcate regimes where global contagions become possible for networks of arbitrary size. Our results draw parallels between the competition of genes in a population and memes in a world of minds and ideas. Our tools provide insight into the spread of information, behaviors, and ideas via social influence, and highlight the role of macroscopic network structure in determining their fate.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Gyrokinetic simulation of low-frequency Alfvénic modes in DIII-D tokamak

Global gyrokinetic simulations find that a beta-induced Alfvén eigenmode (BAE) and a Low frequency mode (LFM) coexist in the DIII-D tokamak experiments. The LFM can be excited without fast ions and has a frequency inside the gap of the beta-induced Alfvén-acoustic eigenmode (BAAE). The mode structure of the LFM from simulations and many of its parametric dependencies are consistent with experimental observations. For the BAE, the simulated mode structure is consistent with experiment but the frequency is lower than experiment. An antenna scan shows that the LFM is NOT the conventioanl BAAE; rather, it is an interchange-like electromagnetic mode excited by non-resonant drive of pressure gradients. The compressible magnetic perturbations significantly increase the growth rates of the BAE and LFM. On the other hand, effects of trapped electrons and equilibrium current have modest effects on the BAE and LFM. Finally, radial transfer of wave energy is different between the BAE and LFM, resulting in their respective triangular and elliptic mode shapes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Simulation of the NaGd(MoO{sub 4}){sub 2}–NaEu(MoO{sub 4}){sub 2} and Na{sub 2}Gd{sub 4}(MoO{sub 4}){sub 7}–Na{sub 2}Eu{sub 4}(MoO{sub 4}){sub 7} Solid Solutions by the Interatomic Potential Method

Simulation of the solid solutions in the system of double sodium–gadolinium and sodium–europium molybdates, which are promising matrices for solid state lasers and phosphors has been carried out by the method of interatomic potentials. Two types of solid solutions have been studied, one of which contains finite components corresponding to the stoichiometric NaGd(MoO{sub 4}){sub 2}–NaEu(MoO{sub 4}){sub 2} compositions with statistical distribution of cations in the crystal lattice. Another object is a cation-deficient Na{sub 2}Gd{sub 4}(MoO{sub 4}){sub 7}–Na{sub 2}Eu{sub 4}(MoO{sub 4}){sub 7} system, in which we have examined the variants of statistical distribution and partial ordering of cations over structural positions. Atomistic simulation has been performed using the GULP 4.0.1 software package (General Utility Lattice Program). It is shown that when we pass from sodium-gadolinium molybdate to sodium-europium molybdate, both of stoichiometric and cation-deficient compositions, an increase in the unit cell volume is observed, while the density of the crystal, the energy of interatomic interactions in the structure, the vibrational entropy and the heat capacity decrease along with increasing europium content. The energy of interatomic interactions in the structure for cation-deficient solid solutions is less than for stoichiometric ones. Other aforementioned characteristics for cation-deficient solid solutions have greater values than for stoichiometric ones. The role of cluster europium centers in concentration quenching in NaGd(MoO{sub 4}){sub 2}–NaEu(MoO{sub 4}){sub 2} solid solutions has been examined.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Liquid crystal torons in Poiseuille-like flows

Three-dimensional (3D) simulations of the structure of liquid crystal (LC) torons, topologically protected distortions of the LC director field, under material flows are rare but essential in microfluidic applications. Here, we show that torons adopt a steady-state configuration at low flow velocity before disintegrating at higher velocities, in line with experimental results. Furthermore, we show that under partial slip conditions at the boundaries, the flow induces a reversible elongation of the torons, also consistent with the experimental observations. These results are in contrast with previous simulation results for 2D skyrmions under similar flow conditions, highlighting the need for a 3D description of this LC soliton in relation to its coupling to the material flow. These findings pave the way for future studies of other topological solitons, like hopfions and heliknotons, in flowing soft matter systems.

Science & Technology - Other Topics↗
DOE OSTI2020

Realistic Ion Dynamics through Charge Renormalization in Nonaqueous Electrolytes

While many practically important electrolytes contain lithium ions, interactions of these ions are particularly difficult to probe experimentally because of their small X-ray and neutron scattering cross sections and large neutron absorption cross sections. Molecular dynamics (MD) is a powerful tool for understanding the properties of nonaqueous electrolyte solutions from the atomic level, but the accuracy of this computational method crucially depends on the physics built into the classical force field. In this study, we demonstrate that several force fields for lithium bistriflimide (LiTFSI) in acetonitrile yield a solution structure that is consistent with the neutron scattering experiments, yet these models produce dramatically different ion dynamics in solution. Such glaring discrepancies indicate that inadequate representation of long-range interactions leads to excessive ionic association and ion-pair clustering. We show that reasonable agreement with the experimental observations can be achieved by renormalization of the ion charges using a “titration” method suggested herewith. This simple modification produces realistic concentration dependencies for ionic diffusion and conductivity in <2 M solutions, without loss in quality for simulation of the structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Predictions of Boron Phase Stability Using an Efficient Bayesian Machine Learning Interatomic Potential

Thermodynamic phase stability of three elemental boron allotropes, i.e., α-B, β-B, and γ-B, was investigated using a Bayesian interatomic potential trained via a sparse Gaussian process (SGP). SGP potentials trained with datasets from on-the-fly active learning achieve quantum mechanical level accuracy when employed in molecular dynamics simulations to predict wide-ranging thermodynamic, structural, and vibrational properties. The simulated phase diagram (500~1400 K and 0~16 GPa) agrees with experimental measurements. The SGP-based MD simulations also successfully predicted that the B13 defect is critical in stabilizing β-B below 700 K. At higher temperatures, the entropy becomes the dominant factor, making β-B the more stable phase over α-B. Furthermore, this Letter demonstrates that SGP potentials based on a training set consisting of defect-free-only systems could make correct predictions of defect-related phenomena in solid-state crystals, paving the path to investigate crystal phase stability and transitions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Mechanism of DNA origami folding elucidated by mesoscopic simulations

Abstract Many experimental and computational efforts have sought to understand DNA origami folding, but the time and length scales of this process pose significant challenges. Here, we present a mesoscopic model that uses a switchable force field to capture the behavior of single- and double-stranded DNA motifs and transitions between them, allowing us to simulate the folding of DNA origami up to several kilobases in size. Brownian dynamics simulations of small structures reveal a hierarchical folding process involving zipping into a partially folded precursor followed by crystallization into the final structure. We elucidate the effects of various design choices on folding order and kinetics. Larger structures are found to exhibit heterogeneous staple incorporation kinetics and frequent trapping in metastable states, as opposed to more accessible structures which exhibit first-order kinetics and virtually defect-free folding. This model opens an avenue to better understand and design DNA nanostructures for improved yield and folding performance.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Galaxy formation with wave/fuzzy dark matter: The core-halo structure and the solitonic imprint

Dark matter-dominated cores have long been claimed for the well-studied local group dwarf galaxies. More recently, extended stellar halos have been uncovered around several of these dwarfs through deeper imaging and spectroscopy. Such core-halo structures (inner flat core and a characteristic r −3 asymptotic outer halo profile) are not a feature of conventional cold dark matter (CDM). In contrast, smooth and prominent dark matter cores are predicted for wave/fuzzy dark matter (ψDM). The question arises as to what extent the visible stellar profiles should reflect this dark matter core structure. Here we compare cosmological hydrodynamical simulations of CDM, “WDM” (model used as a proxy for ψDM) & ψDM, aiming to predict the stellar profiles for these three DM scenarios. We show that cores surrounded by extended halos are distinguishable for ψDM, where the stellar density is enhanced in the core due to the presence of the relatively dense soliton. Our analysis demonstrates that, in our simulations, a distinctive core-halo structure does not appear in the case of CDM in the DM, gas, or stars. Whereas we do find a core-halo transition for DM, gas, and stars for ψDM, and the scale of this transition is in line with the predicted core radius set by the soliton scale anticipated for the adopted boson mass of 2.5×10 −22 eV. The presence of a core-halo structure in the stellar profile for Galaxy 1 for ψDM is visible for the most massive and the first galaxy to form in the simulation. Clearly, further simulations are needed to establish how strict this possible relationship is between the DM and stellar core-halo profile as a potential observational discriminator. Furthermore, we observe the anticipated asymmetry for ψDM due to the soliton's motion (jumping and random walk), a distinctive characteristic not found in the symmetric distributions of stars in the warm and CDM models.

dark matter↗
DOE OSTI2024

Complex Structure of Molten FLiBe (2 Li F – Be F 2 ) Examined by Experimental Neutron Scattering, X-Ray Scattering, and Deep-Neural-Network Based Molecular Dynamics

The use of molten salts as coolants, fuels, and tritium breeding blankets in the next generation of fission and fusion nuclear reactors benefits from furthering the characterization of the molecular structure of molten halide salts, paving the way to predictive capability of the chemical and thermophysical properties of molten salts. Due to its neutronic, chemical, and thermochemical properties, 2 Li F - Be F 2 is a candidate molten salt for several fusion- and fission-reactor designs. We performed neutron and x-ray total-scattering measurements to determine the atomic structure of liquid 2 Li F - Be F 2 . We also performed and neural-network molecular-dynamics simulations to predict the structure obtained by neutron- and x-ray-diffraction experiments. The use of machine learning provides improvements to the efficiency in predicting the structure at a longer length scales than is achievable with simulations at significantly lower computational expense while retaining near accuracy. We found that the NNMD simulations accurately predicted the Be F 4 2 − oligomer formations seen in the experimental first-structure-factor peak. Our combination of high-resolution measurements with large-scale molecular dynamics provided an avenue to explore and experimentally verify the intermediate-range ordering beyond the first-nearest neighbor that has posed too many experimental and computational challenges in previous works. With a deeper understanding of the salt structure and ion ordering, the evolution of salt chemistry over the lifetime of a reactor can be better predicted, which is crucial to the licensing and operation of advanced fission and fusion reactors that employ molten salts. To this end, this work will serve as a reference for future studies of salt structure and macroscopic properties with and without the addition of solutes. Published by the American Physical Society 2024

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

A fully-integrated lattice Boltzmann method for fluid–structure interaction

Here we present a fully-integrated lattice Boltzmann (LB) method for fluid–structure interaction (FSI) simulations that efficiently models deformable solids in complex suspensions and active systems. Our Eulerian method (LBRMT) couples finite-strain solids to the LB fluid on the same fixed computational grid with the reference map technique (RMT). An integral part of the LBRMT is a new LB boundary condition for moving deformable interfaces across different densities. With this fully Eulerian solid–fluid coupling, the LBRMT is well-suited for parallelization and simulating multi-body contact without remeshing or extra meshes. We validate its accuracy via a benchmark of a deformable solid in a lid-driven cavity, then showcase its versatility through examples of soft solids rotating and settling. The LBRMT achieves a spatial convergence rate between first-order and second-order for FSI simulations and is designed for low to intermediate Reynolds number flows with finite inertia at small Mach numbers. With simulations of complex suspensions mixing, we highlight the potential of the LBRMT for studying collective behavior in soft matter and biofluid dynamics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Investigation of the Effect of Temperature on the Structure of SARS-CoV-2 Spike Protein by Molecular Dynamics Simulations

Statistical and epidemiological data imply temperature sensitivity of the SARS-CoV2 coronavirus. However, the molecular level understanding of the virus structure at different temperature is still not clear. Spike protein is the outermost structural protein of the SARS-CoV-2 virus which interacts with the Angiotensin Converting Enzyme 2 (ACE2), a human receptor, and enters the respiratory system. In this study, we performed an all atom molecular dynamics simulation to study the effect of temperature on the structure of the Spike protein. After 200 ns of simulation at different temperatures, we came across some interesting phenomena exhibited by the protein. We found that the solvent exposed domain of Spike protein, namely S1, is more mobile than the transmembrane domain, S2. Structural studies implied the presence of several charged residues on the surface of N-terminal Domain of S1 which are optimally oriented at 10– 30°C. Bioinformatics analyses indicated that it is capable of binding to other human receptors and should not be disregarded. Additionally, we found that receptor binding motif (RBM), present on the receptor binding domain (RBD) of S1, begins to close around temperature of 40°C and attains a completely closed conformation at 50°C. We also found that the presence of glycan moieties did not influence the observed protein dynamics. Nevertheless, the closed conformation disables its ability to bind to ACE2, due to the burying of its receptor binding residues. Our results clearly show that there are active and inactive states of the protein at different temperatures. This would not only prove beneficial for understanding the fundamental nature of the virus, but would be also useful in the development of vaccines and therapeutics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Smoothened stimulation by membrane sterols drives Hedgehog pathway activity

Hedgehog signalling is fundamental to embryonic development and postnatal tissue regeneration. Aberrant postnatal Hedgehog signalling leads to several malignancies, including basal cell carcinoma and paediatric medulloblastoma. Hedgehog proteins bind to and inhibit the transmembrane cholesterol transporter Patched-1 (PTCH1), which permits activation of the seven-transmembrane transducer Smoothened (SMO) via a mechanism that is poorly understood. Here we report the crystal structure of active mouse SMO bound to both the agonist SAG21k and to an intracellular binding nanobody that stabilizes a physiologically relevant active state. Analogous to other G protein-coupled receptors, the activation of SMO is associated with subtle motions in the extracellular domain, and larger intracellular changes. In contrast to recent models, a cholesterol molecule that is critical for SMO activation is bound deep within the seven-transmembrane pocket. We propose that the inactivation of PTCH1 by Hedgehog allows a transmembrane sterol to access this seven-transmembrane site (potentially through a hydrophobic tunnel), which drives the activation of SMO. Overall, these results—combined with signalling studies and molecular dynamics simulations—delineate the structural basis for PTCH1–SMO regulation, and suggest a strategy for overcoming clinical resistance to SMO inhibitors.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Elucidating the formation mechanisms of zeolites using data-driven modelling and in-situ characterization

Zeolites are the main solid catalysts used by the chemical industry. The use of zeolites in separations and as shape selective catalysts requires control of the width and connectivity of their pores. 235 distinct zeolite frameworks have been synthesized to date, of over 2 million that have been proposed. Recent work indicates that the limitation is in large part kinetic: new synthetic pathways are required to access new zeolites. Organic cations are used to direct the synthesis towards specific zeolites. However, the molecular mechanisms by which cations direct the nucleation towards specific zeolites is not known. Elucidating these mechanisms is key to realize new zeolites for catalysis and separations, and is the focus of this project. This project developed and implemented a synergistic, data-driven computational and experimental approach to resolve the molecular pathways of nucleation, growth, and polymorph selection of zeolites and the role of organic cations in directing their formation. The project developed computationally efficient and accurate models for the study of the nucleation and growth of pure silica zeolites in molecular simulations, using machine learning with data from experiments. Simulations with these models were integrated with scanning tunneling electron microscopy, computer vision, and deep learning to unveil the molecular pathways of formation of a zeolite. Of particular interest in this project was to elucidate the role of amorphous precursors in the nucleation of the zeolite. Previous experiments indicate that zeolites are born within non-crystalline aggregates in which the silicates and organic cations have local and medium range order similar to that of the zeolite. The organic cations that direct the formation of zeolites and those that direct the formation of ordered mesoporous silicas are similar. We hypothesized that the frustrated attraction that for large organic cations leads to the formation of stable mesophases that direct the synthesis of mesoporous silicas, could promote the formation of metastable mesophases that can assist in the nucleation and polymorph selection of zeolites. The simulations resolved how structure directing agents build crystalline order and showed that mesoscopic pre-ordering occurs is not required to facilitate the nucleation of zeolites, because the synthesis occurs at high driving forces, where the barriers for nucleation are negligible. This project unveiled that polymorph selection in zeolite synthesis occurs after nucleation, opening a distinct area of control through the kinetics of growth and not through nucleation barriers.

36 MATERIALS SCIENCE↗
DOE OSTI2024

An Open-Source Parallel EMT Simulation Framework

As the integration level of inverter-based resources (IBRs) increases, ensuring the reliable operation of the bulk power systems requires the use of electromagnetic transient (EMT) simulation tools to identify and mitigate system-wide stability risks. Conducting EMT studies for large-scale, IBR-rich grids, however, is challenging due to the inherent computational bottleneck caused by the underlying high-fidelity models and required small time steps. This paper introduces ParaEMT: an open-source, generic EMT simulation framework designed to accelerate simulations by leveraging advanced parallel computational technologies, such as high-performance computers. This paper presents a comprehensive exposition of ParaEMT, covering its modeling library, simulation strategy, framework structure, operational procedures, and auxiliary features, alongside its extensible parallel computational architecture. Notably, ParaEMT is a publicly accessible and modularized framework written in Python, thereby facilitating future development and the integration of new models and algorithms. The accuracy and efficiency of ParaEMT are demonstrated by rigorous validations via multiple case studies.

electromagnetic transient simulation↗
DOE OSTI2023

An Open-Source Parallel EMT Simulation Framework: Preprint

As the integration level of inverter-based resources (IBR) increases, ensuring the reliable operation of the bulk power systems requires the use of electromagnetic transient (EMT) simulation tools to identify and mitigate system-wide stability risks. Conducting EMT studies for large-scale, IBR-rich grids, however, is challenging due to the inherent computational bottleneck caused by the underlying high-fidelity models and required small time steps. This paper introduces ParaEMT: an open-source, generic EMT simulation framework designed to accelerate simulations by leveraging advanced parallel computational technologies, such as high-performance computers. This paper presents a comprehensive exposition of ParaEMT, covering its modeling library, simulation strategy, framework structure, operational procedures, and auxiliary features, alongside its extensible parallel computational architecture. Notably, ParaEMT is a publicly accessible and modularized framework written in Python, thereby facilitating future development and the integration of new models and algorithms. The accuracy and efficiency of ParaEMT are demonstrated by rigorous validations via multiple case studies.

electromagnetic transient simulation↗