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At least 1,477 records · Page 82

Simulation capability for dynamics of rotating counterweight space stations.

An analysis and computer program were prepared to realistically simulate the dynamic behavior of a class of space stations consisting of two end bodies separated by a connecting structure. The shape and mass distribution of the flexible end bodies are arbitrary; the connecting structure is flexible but massless and is capable of deployment and retraction. Fluid flowing in a piping system and rigid moving masses, representing a cargo elevator or crew members, have been modeled. Connecting structure characteristics, control systems, and externally applied loads are modeled in easily replaced subroutines. Subroutines currently available include a telescopic beam-type connecting structure as well as attitude, deployment, spin, and wobble control. In addition, a unique mass balance control system was developed to sense and balance mass shifts due to the motion of a cargo elevator. The mass of the cargo may vary through a large range. Numerical results are discussed for various types of runs.

Austin, F.↗

Machine learning force field model for kinetic Monte Carlo simulations of itinerant Ising magnets

Here, we present a scalable machine learning (ML) framework for large-scale kinetic Monte Carlo (kMC) simulations of itinerant electron Ising systems. As the effective interactions between Ising spins in such itinerant magnets are mediated by conducting electrons, the calculation of energy change due to a local spin update requires solving an electronic structure problem. Such repeated electronic structure calculations could be overwhelmingly prohibitive for large systems. Assuming the locality principle, a convolutional neural network (CNN) model is developed to directly predict the effective local field and the corresponding energy change associated with a given spin update based on Ising configuration in a finite neighborhood. As the kernel size of the CNN is fixed at a constant, the model can be directly scalable to kMC simulations of large lattices. Our approach is reminiscent of the ML force field models widely used in first-principles molecular dynamics simulations. Applying our ML framework to a square-lattice double-exchange Ising model, we uncover unusual coarsening of ferromagnetic domains at low temperatures. Our work highlights the potential of ML methods for large-scale modeling of similar itinerant systems with discrete dynamical variables.

machine learning↗

Thermal-Fluid and Thermal-Structural Response of the T-Tube Modular Divertor to Spatiotemporally Varying Heat Loads

Tungsten (W) is the leading candidate for divertor target plates because of its high melting point (>3000°C), thermal conductivity, and ultimate tensile stress. While W and its alloys are the only solid materials that can survive the high heat fluxes incident on the divertor, W’s low-ductility high ductile-to-brittle transition temperature of ~600°C and relatively low recrystallization temperature (RT) of ~1300°C pose structural (among other) challenges. The objective of this work is to estimate the thermal-fluid and thermal-structural performance of the helium (He)-cooled T-tube divertor, which was originally developed by the Advanced Reactor Innovation and Evaluation Study (ARIES) using numerical simulations. Here, predictions of temperature distributions across the plasma-facing structural component and surface pressures from computational fluid dynamics simulations are used to determine stress distributions using commercial structural finite element modeling software over a range of fusion-relevant conditions. The maximum allowable incident heat fluxes are determined based on the temperature limits imposed by the ITER elastic Structural Design Criteria for In-vessel Components (SDC-IC) and the maximum RT over a range of He mass flow rates and presented in the form of performance design charts. Our recent work found that thermal- structural criteria accounting for the low ductility of W in a finger-type modular divertor constrain the maximum incident heat fluxes to values well below the ITER specifications, and those based on considering only the RT demonstrate that integrated thermal-fluid and elastic structural performance evaluation are required for accurate assessment of divertor performance. This novel analysis of the T-tube considers how nonuniform and transient incident heat fluxes affect its thermal-fluid and thermal-structural performance, as well as the effect of volumetric heating, which can be as great as 27% of the power incident on the divertor surface. The W tile of the T-tube, with its relatively large plasma-facing area of ~15 cm 2 , will likely experience significant spatial variations in incident heat flux. This work therefore assesses whether steady-state incident heat flux profiles with a peak of 10 MW/m 2 and maximum heat flux gradients of 200 MW/m 2 per m exceed the structural limits imposed by the ITER elastic SDC-IC and the maximum RT over a range of fusion-relevant conditions. The effect of transient heat fluxes typical of plasma detachment and reattachment from the target plate due, for example, to gas injection are also evaluated

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Enhanced dynamic equivalent identification method of large-scale power systems using multiple events

The increasing complexity of the interconnected power system makes high-fidelity dynamic simulation models computationally more intensive. To improve computation efficiency, model reduction techniques have been investigated to only preserve the dynamics in a limited area of interest (study area), while deriving equivalent representation for the external area. For this purpose, a measurement-based reduction approach using system identification techniques has been previously proposed. Accordingly, external areas are represented by dynamic equivalent loads using transfer function estimation. In this paper, in order to enhance the accuracy of the reduced model in preserving dynamics of the study area, multiple “grid” events of different types and at different locations are considered for identifying the parameters of the equivalent loads. Additionally, case studies are carried out in the NPCC 140-bus system. Comparisons are made between multiple events training and single event training, highlighting the advantages of the proposed method in providing a better representation of the grid dynamics under different operating conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Hard–Soft Acid–Base Theory Explains Photoexcited Carrier Dynamics in Porphyrin/CNT Nanohybrids: Time-Domain Atomistic Analysis

We employ the fundamental chemical concepts of hard− soft acid−base to formulate general principles governing excited-state dynamics in zinc porphyrin (ZnP)/carbon nanotube (CNT) hybrids for energy photoconversion. Atomistic quantum dynamics simulations demonstrate that electron-withdrawing and donating substituents at the ZnP β-pyrrolic position strongly influence the dynamics. ZnP photoexcitation produces subpicosecond electron transfer (ET) from ZnP to CNT, in agreement with the experiment. Substitutions of CN by H and tBu accelerate the ET. The trend is directly related to the hard−soft acid−base concept because the soft−soft interaction between the t Bu- ZnP acid and the mild CNT base enhances the donor−acceptor coupling. Longer coherence and more active vibrational modes facilitate the ET in t Bu-ZnP/CNT. Electron−hole recombination in CN-ZnP/CNT occurs on a hundred picosecond time scale, nicely corroborated by the experiment. The exciton lifetime is extended beyond a nanosecond by the substitutions. The soft−soft interaction in t Bu-ZnP/ CNT increases the splitting between the highest occupied orbitals of the two subsystems, reduces their mixing, and decreases nonadiabatic coupling between the ground and excited states. Rapid decoherence and involvement of low-frequency vibrations favor longer lifetimes. Our investigation reveals that larger p K a of the β-pyrrolic acid gives rapid ET and slow recombination and provides detailed mechanistic information, essential for future optoelectronic applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Interplay of molecular dynamics and radiative decay of a TADF emitter in a glass-forming liquid

Herein we investigate the role of molecular dynamics in the luminescent properties of a prototypical thermally activated delayed fluorescence (TADF) emitter, NAI-DMAC, in solution using a combination of temperature dependent time-resolved photoluminescence and absorption spectroscopies. We use a glass forming liquid, 2-methylfuran, to introduce an abrupt change in the temperature dependent diffusion dynamics of the solvent and examine the influence this has on the emission intensity of NAI-DMAC molecules. Comparison of experiment with first principles molecular dynamics simulations reveals that the emission intensity of NAI-DMAC molecules follows the temperature-dependent self-diffusion dynamics of the solvent. A marked reduction of emission intensity is observed as the temperature decreases toward the glass transition because the rate at which NAI-DMAC molecules can access emissive molecular conformations is greatly reduced. Below the glass transition, the diffusion dynamics of the solvent changes more slowly with temperature, which causes the emission intensity to decrease more slowly as well. The combination of experiment and computation suggests a pathway by which TADF emitters may transiently access a distribution of conformational states and avoid the need for an average conformation that strikes a balance between lower singlet–triplet energy splittings versus higher emission probabilities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Chemical evolution in nitrogen shocked beyond the molecular stability limit

Evolution of nitrogen under shock compression up to 100 GPa is revisited via molecular dynamics simulations using a machine-learned interatomic potential. The model is shown to be capable of recovering the structure, dynamics, speciation, and kinetics in hot compressed liquid nitrogen predicted by first-principles molecular dynamics, as well as the measured principal shock Hugoniot and double shock experimental data, albeit without shock cooling. Our results indicate that a purely molecular dissociation description of nitrogen chemistry under shock compression provides an incomplete picture and that short oligomers form in non-negligible quantities. Finally, this suggests that classical models representing the shock dissociation of nitrogen as a transition to an atomic fluid need to be revised to include reversible polymerization effects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Species Separation and Hydrogen Streaming upon Shock Release from Polystyrene under Inertial Confinement Fusion Conditions

Shock release from inertial confinement fusion (ICF) shells poses a great challenge to single-fluid hydrodynamic equations, especially for describing materials composed of different ion species. This has been evidenced by a recent experiment [Haberberger et al., Phys. Rev. Lett. 123, 235001 (2019)], in which low-density plasmas ( 10 19 to 10 20 cm – 3 ) are measured to move far ahead of what radiation-hydrodynamic simulations predict. To understand such experimental observations, in this work we have performed large-scale nonequilibrium molecular-dynamics simulations of shock release in polystyrene (CH) at experimental conditions. These simulations revealed that upon shock releasing from the back surface of a CH foil, hydrogen can stream out of the bulk of the foil due to its mass being lighter than carbon. This released hydrogen, exhibiting a much broader velocity distribution than carbon, forms low-density plasmas moving in nearly constant velocities ahead of the in-flight shell, which is in quantitative agreement with the experimental measurements. Such kinetic effect of species separation is currently missing in single-fluid radiation-hydrodynamics codes for ICF simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Lewis hybrid computing system, users manual

The Lewis Research Center's Hybrid Simulation Lab contains a collection of analog, digital, and hybrid (combined analog and digital) computing equipment suitable for the dynamic simulation and analysis of complex systems. This report is intended as a guide to users of these computing systems. The report describes the available equipment' and outlines procedures for its use. Particular is given to the operation of the PACER 100 digital processor. System software to accomplish the usual digital tasks such as compiling, editing, etc. and Lewis-developed special purpose software are described.

Bruton, W. M.↗

Space tethers for science in the space station era; Proceedings of the Second International Conference, Venice, Italy, Oct. 4-8, 1987

Various papers on space tethers are presented. The general topics addressed include: the space program context for tethers, early experimental validation of tethers, tether dynamics simulations, electrodynamics aspects of tethers, and tethers for science and innovative uses. Also considered are: tethers in space, tether dynamics, tethers on stations and platforms, and tether technology.

Guerriero, Luciano↗

Analysis of Ice Mass Growth Over Time on the CRM65 Midspan Hybrid Model

The Aeronautics Research Mission Directorate at NASA is developing and applying tools to enable future technologies towards sustainable flight. Aircraft icing has been identified as a potential barrier to entry into service for innovative designs necessitating improvements to computational ice accretion tools. NASA is developing the Glenn Icing Computational Environment (GlennICE) to address deficiencies in the computational modeling capabilities of previously developed ice accretion solvers. To benchmark and improve the ability to model highly three-dimensional ice accretion, high quality validation data against experimental data is required. The CRM65 Midspan Hybrid geometry was previously tested at the NASA Icing Research Tunnel to generate experimental data for swept wing geometries typical for commercial transport aircraft. As a part of a 2018 icing test campaign, experimental data characterizing the relationship between ice accretion time and ice mass growth was obtained and can be leveraged for use in validation of computational tools. The desire for computational ice accretion solvers to predict ice shapes profiles accreted experimentally has often overshadowed the comparison to the mass and bulk volume of ice accreted. To address this deficiency, an analysis is presented in which GlennICE is applied to simulations of the CRM65 Midspan Hybrid model tested in the NASA Icing Research Tunnel. Results from the computational fluid dynamics simulations compared favorably to the experimental pressure coefficient data, thus validating the modeling setup. The experimental data showed excellent repeatability for the 15.0 minute accretion time. The comparisons between the experimental and computational ice mass over time showed good agreement up to 10.0 minutes after which the ice mass was underpredicted. The experimental ice mass was largely linear with some nonlinear data. The bulk volume of ice accreted experimentally compared well to GlennICE for the scanned ice shapes and mean combined cross section ice shapes, but was underpredicted for the maximum combined cross section ice shapes at longer accretion times. The experimental minimum combined cross section, mean combined cross section, and maximum combined cross section profiles when compared to GlennICE show good agreement for the mean combined cross section up to 15.0 minutes. The analyses show that with a single-shot method, GlennICE currently underpredicts the ice mass for longer accretion times, is not able to match the bulk volume of the maximum combined cross section due to dominating scallop features, and future work is required to generate a more generalized ice bulk density model.

Icing↗

Analysis of Ice Mass Growth Over Time on the CRM65 Midspan Hybrid Model

The Aeronautics Research Mission Directorate at NASA is developing and applying tools to enable future technologies towards sustainable flight. Aircraft icing has been identified as a potential barrier to entry into service for innovative designs necessitating improvements to computational ice accretion tools. NASA is developing the Glenn Icing Computational Environment (GlennICE) to address deficiencies in the computational modeling capabilities of previously developed ice accretion solvers. To benchmark and improve the ability to model highly three-dimensional ice accretion, high quality validation data against experimental data is required. The CRM65 Midspan Hybrid geometry was previously tested at the NASA Icing Research Tunnel to generate experimental data for swept wing geometries typical for commercial transport aircraft. As a part of a 2018 icing test campaign, experimental data characterizing the relationship between ice accretion time and ice mass growth was obtained and can be leveraged for use in validation of computational tools. The desire for computational ice accretion solvers to predict ice shapes profiles accreted experimentally has often overshadowed the comparison to the mass and bulk volume of ice accreted. To address this deficiency, an analysis is presented in which GlennICE is applied to simulations of the CRM65 Midspan Hybrid model tested in the NASA Icing Research Tunnel. Results from the computational fluid dynamics simulations compared favorably to the experimental pressure coefficient data, thus validating the modeling setup. The experimental data showed excellent repeatability for the 15.0 minute accretion time. The comparisons between the experimental and computational ice mass over time showed good agreement up to 10.0 minutes after which the ice mass was underpredicted. The experimental ice mass was largely linear with some nonlinear data. The bulk volume of ice accreted experimentally compared well to GlennICE for the scanned ice shapes and mean combined cross section ice shapes, but was underpredicted for the maximum combined cross section ice shapes at longer accretion times. The experimental minimum combined cross section, mean combined cross section, and maximum combined cross section profiles when compared to GlennICE show good agreement for the mean combined cross section up to 15.0 minutes. The analyses show that with a single-shot method, GlennICE currently underpredicts the ice mass for longer accretion times, is not able to match the bulk volume of the maximum combined cross section due to dominating scallop features, and future work is required to generate a more generalized ice bulk density model.

Icing↗

Enhanced Dynamic Equivalent Identification Method of Large-Scale Power Systems Using Multiple Event

The increasing complexity of the interconnected power system makes high-fidelity dynamic simulation models computationally more intensive. To improve computation efficiency, model reduction techniques have been investigated to only preserve the dynamics in a limited area of interest (study area), while deriving equivalent representation for the external area. For this purpose, a measurement-based reduction approach using system identification techniques has been previously proposed. In that case, external areas are represented by dynamic equivalent loads using transfer function estimation. In this paper, in order to enhance the accuracy of the reduced model in preserving dynamics of the study area, multiple “grid” events of different types and at different locations are considered for identifying the parameters of the equivalent loads. Case studies are carried out in the NPCC 140-bus system. Comparison are made between multiple events training and single event training, highlighting the advantages of the proposed method in providing a better representation of the grid dynamics under different operating conditions.

Xue, Yaosuo↗

Molecular simulation of the separation of toluene and p-xylene with the thermally-robust ionic liquid triphenyl-p-phenyl sulfonyl phenyl phosphonium

In this work, we use molecular dynamics simulations to evaluate the behavior of toluene (TOL) and p-xylene (XYL) within three different solvents: n -hexane (HEX), n -heptane (HEP), and a thermally-robust ionic liquid (triphenyl-p-phenyl sulfonyl phenyl phosphonium + bis(trifluoromethylsulfonyl)imide (TPSP + Tf 2 N)). Several different temperatures are explored, while the solvation structures, energetics, and dynamics of TOL and XYL are evaluated. The solvation free energy (ΔG solv ) and transfer free energy (ΔG transfer ) of TOL and XYL are calculated using thermodynamic integration (TI). The transfer free energy of XYL from HEP/HEX to TPSP + Tf 2 N is more favorable than that of TOL over the entire temperature range, while the transfer of both TOL and XYL becomes less favorable as the temperature increases. The diffusion rates of TOL and XYL are lower in the ionic liquid when compared to HEP and HEX, but the thermal stability of TPSP + Tf 2 N may allow for higher operating temperatures and accelerated mass transport rates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Electro-reduction of organics on metal cathodes: A multiscale-modeling study of benzaldehyde on Au (111)

Here, we present a multiscale modeling study on the electro-reduction of benzaldehyde (BZY) on Au(111) under realistic electrochemical conditions. To model the electrochemical cell, we adopt a capacitor model in which complex solvents are confined between a Au cathode and a carbon anode. Classical molecular dynamics simulations reveal that electrode charge density and the presence of alcohol show strong effects on the density, adsorption geometry and dynamics of benzaldehyde on the Au electrode. Under charging conditions, the surface concentration of benzaldehyde on the Au electrode decreases, while the content of other species increases. Finally, we proposed a scheme that correlates the electric current running through the Au/solvent interface with the applied bias. This study provides a molecular level understanding of how solvent composition, in this case water/alcohol content, controls the activity of electrocatalytic hydrogenation

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

QMMM 2023: A program for combined quantum mechanical and molecular mechanical modeling and simulations

Combined quantum mechanical and molecular mechanical (QM/MM) methods play an important role in multiscale modeling and simulations. QMMM 2023 is a general-purpose program for single-point calculations, geometry optimizations, transition-state optimizations, and molecular dynamics (MD) at the QM/MM level. It calls a QM package and an MM package to perform the required single-level calculations and combines them into a QM/MM energy by a variety of schemes. QMMM 2023 supports GAMESS-US, Gaussian, and ORCA as QM packages and Tinker as the MM package. Four types of treatments are available for embedding the QM subsystem in the MM environment: mechanical embedding with gas-phase calculations of the QM region, electronic embedding that allows polarization of the QM region by the MM environment, polarizable embedding for mutual polarization of the QM and MM regions, and flexible embedding for both mutual polarization and partial charge transfer between the QM and MM regions. Boundaries between QM and MM regions that pass through covalent bonds can be treated by several methods, including the redistributed charge (RC) scheme, redistributed charge and dipole (RCD) scheme, balanced-RC scheme, balanced-RCD scheme, screened charge scheme that takes account of charge penetration effects, and smeared charge scheme that delocalizes the MM charges near the QM–MM boundary. Geometry optimization can be done using the optimizer implemented in QMMM 2023 or the Berny optimizer in Gaussian through external calls to Gaussian. Molecular dynamics simulations can be performed at the pure-MM level, pure-QM level, fixed-partitioning QM/MM level, and adaptive-partitioning QM/MM level. As a result, the adaptive-partitioning treatments permit on-the-fly relocation of the QM–MM boundary by dynamically reclassifying atoms or groups into the QM or MM subsystems.

97 MATHEMATICS AND COMPUTING↗

Short-wavelength-sensitive 2 (Sws2) visual photopigment models combined with atomistic molecular simulations to predict spectral peaks of absorbance

For many species, vision is one of the most important sensory modalities for mediating essential tasks that include navigation, predation and foraging, predator avoidance, and numerous social behaviors. The vertebrate visual process begins when photons of the light interact with rod and cone photoreceptors that are present in the neural retina. Vertebrate visual photopigments are housed within these photoreceptor cells and are sensitive to a wide range of wavelengths that peak within the light spectrum, the latter of which is a function of the type of chromophore used and how it interacts with specific amino acid residues found within the opsin protein sequence. Minor differences in the amino acid sequences of the opsins are known to lead to large differences in the spectral peak of absorbance (i.e. the λ max value). In our prior studies, we developed a new approach that combined homology modeling and molecular dynamics simulations to gather structural information associated with chromophore conformation, then used it to generate statistical models for the accurate prediction of λ max values for photopigments derived from Rh1 and Rh2 amino acid sequences. In the present study, we test our novel approach to predict the λ max of phylogenetically distant Sws2 cone opsins. To build a model that can predict the λ max using our approach presented in our prior studies, we selected a spectrally-diverse set of 11 teleost Sws2 photopigments for which both amino acid sequence information and experimentally measured λ max values are known. The final first-order regression model, consisting of three terms associated with chromophore conformation, was sufficient to predict the λ max of Sws2 photopigments with high accuracy. This study further highlights the breadth of our approach in reliably predicting λ max values of Sws2 cone photopigments, evolutionary-more distant from template bovine RH1, and provided mechanistic insights into the role of known spectral tuning sites.

59 BASIC BIOLOGICAL SCIENCES↗

Effects of pore size on water dynamics in mesoporous silica

Water confined in mesoporous silica plays a central role in its many uses ranging from gas sorption to nanoconfined chemical reactions. Here in this paper, the influence of pore diameter (2.5–5.4 nm) on water hydrogen bond (H-bond) dynamics in MCM41 and SBA15 mesoporous silicas is investigated using femtosecond infrared vibrational spectroscopy and molecular dynamics simulations on selenocyanate (SeCN-) anions dissolved in the pores. As shown recently, SeCN- spectral diffusion is a reliable probe of surrounding water H-bond structural motions. Additionally, the long CN stretch vibrational lifetime facilitates measurement of the full range of confined dynamics, which are much slower than in bulk water. The simulations shed light on quantitative details that are inaccessible from the spatially averaged observables. The dependence of SeCN- orientational relaxation and that of spectral diffusion on the distance from the silica interface are quantitatively described with an exponential decay and a smoothed step-function, respectively. The distance-dependence of both quantities is found to be independent of the diameter of the pores, and the spatial distribution of SeCN- is markedly non-uniform, reaching a maximum between the interface and the pore center. The results indicate that the commonly invoked two-state, or core–shell, model is a more appropriate description of spectral diffusion. Using these insights, we model the full time-dependence of the measured dynamics for all pore sizes and extract the “core” and “shell” dynamical correlation functions and SeCN- spatial probability distributions. The results are critically compared to those for water confined in reverse micelles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗