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Prebuckling deformation effects on clamped, thin- walled cylindrical shell buckling due to axial loading and internal pressure
We present a new numerical methodology for simulating fluid–structure interaction (FSI) problems involving thin flexible bodies in an incompressible fluid. The FSI algorithm uses the Dirichlet–Neumann partitioning technique. The curvilinear immersed boundary method (CURVIB) is coupled with a rotation-free finite element (FE) model for thin shells enabling the efficient simulation of FSI problems with arbitrarily large deformation. Turbulent flow problems are handled using large-eddy simulation with the dynamic Smagorinsky model in conjunction with a wall model to reconstruct boundary conditions near immersed boundaries. The CURVIB and FE solvers are coupled together on the flexible solid–fluid interfaces where the structural nodal positions, displacements, velocities and loads are calculated and exchanged between the two solvers. Loose and strong coupling FSI schemes are employed enhanced by the Aitken acceleration technique to ensure robust coupling and fast convergence especially for low mass ratio problems. The coupled CURVIB-FE-FSI method is validated by applying it to simulate two FSI problems involving thin flexible structures: 1) vortex-induced vibrations of a cantilever mounted in the wake of a square cylinder at different mass ratios and at low Reynolds number; and 2) the more challenging high Reynolds number problem involving the oscillation of an inverted elastic flag. For both cases the computed results are in excellent agreement with previous numerical simulations and/or experiential measurements. Grid convergence tests/studies are carried out for both the cantilever and inverted flag problems, which show that the CURVIB-FE-FSI method provides their convergence. Finally, the capability of the new methodology in simulations of complex cardiovascular flows is demonstrated by applying it to simulate the FSI of a tri-leaflet, prosthetic heart valve in an anatomic aorta and under physiologic pulsatile conditions.
Spin-state energetics are important for understanding properties that involve more than one spin state, for example, catalysis occurring on two or more potential energy surfaces corresponding to different electronic spins. Very often, multiple-spin processes involve transition-metal compounds, and therefore, it is important to understand the electronic structure and energetics of such compounds in different spin states. In this work, we benchmark relative spin-state energies of FeF 2 with respect to the quintet ground spin state using both singleconfigurational and multi-configurational methods, and we examine how they are affected by the binding of ethane and ethylene to the iron center. We also benchmark the binding energies of the complexes. The single-configurational methods used in this work are the Hartree–Fock method, 32 exchange–correlation functionals, and the CCSD(T) coupled-cluster method in both restricted and unrestricted formalisms. The multi-configurational methods that have been used are CASSCF, CASPT2, CASPT3, MRCI, MRCI+Q, and MR-ACPF. The spin-state splitting energies depend on the functional chosen and of the 32 exchange-correlation functionals investigated here we find that for the septet and spin-projected triplet states of FeF 2 , the M06 functional is the best when compared to our best estimates from multi-reference calculations. If all the nine excitation energies are considered, where there are three excited spin states (singlet, triplet, and septet) for each of the three systems (FeF 2 , FeF 2 ···ethane, and FeF 2 ···ethylene), the three best performing functionals are HLE16, SOGGA11-X, and M06-2X. We find that the binding of ethane perturbs the relative spin-state energy of FeF 2 by only a small amount, but the stronger binding of ethylene has a larger effect. For the spin-state splitting energies of FeF 2 using single-reference CCSD(T), we found the predicted results depend very strongly on precisely how the calculations are done, in particular, on the spin-restricted or spin-unrestricted character of the SCF reference state, which can differ even by around 50 kcal/mol for the SCF reference state and the subsequent CCSD(T) calculations. Furthermore, on analyzing the wave functions of both the spinrestricted or spin-unrestricted formalisms, we find that the lowest-energy singlet and triplet states of the complexes, just like FeF 2 in isolation, can have more unpaired electrons than they are usually assumed to have, i.e. they can be hyper open-shell electronic configurations, and that this can significantly lower the energy.
When lanthanide ions are present in the aqueous subphase of a floating monolayer (Langmuir film), the ions attracted to the interface will in many cases form commensurate and/or incommensurate two-dimensional structures. These lattices depend not only on the molecules forming the monolayer, but also on the atomic number of the lanthanide, with a sudden change between the lattice formed by lighter ions and that formed by heavier ions under a given monolayer. Since there are few other relevant differences between the lanthanides, we attribute the Z-dependent “transition” to the number of water molecules associated with each ion. Finally, the first hydration shell is thought to vary continuously from ~9 in lighter lanthanides to ~8 in heavier lanthanides.
The kinetics of the oxygen reduction reaction (ORR) was investigated in acid solutions on Pt monolayers that were deposited on carbon-supported Ru nanoparticles using the rotating disk electrode technique. The Pt mass and specific ORR activities greatly depend on the number of Pt monolayers, and the optimum activity occurs with two Pt monolayers. Density functional theory calculations showed that Pt overlayers destabilize O* and OH* with respect to pure Pt, leading to more favorable hydrogenation kinetics. However, with only a single Pt overlayer, the destabilization is too much, and O–O bond breaking becomes rate limiting. Two to three Pt monolayers supported on the Ru core of our nanoparticles lead to increased activity. This work demonstrates that one can modulate the ORR activity of Pt monolayers supported on other metals by eliminating a part of the ligand effect by increasing the thickness of the Pt shell on top of the supporting metal surface.
The selection of oxide materials for catalyzing the Oxygen Evolution Reaction in acid-based electrolyzers must be guided by the proper balance between activity, stability and conductivity – a challenging mission of great importance for delivering affordable and environmentally friendly hydrogen. Here we report that the highly conductive nanoporous architecture of an iridium oxide shell on a metallic iridium core, formed through the fast dealloying of osmium from an Ir 25 Os 75 alloy, exhibits an exceptional balance between oxygen evolution activity and stability as quantified by the Activity-Stability FactorASF. Based on this metric, the nanoporous Ir/IrO 2 morphology of dealloyed Ir 25 Os 75 shows a factor of ~30 improvement ASFrelative to conventional Ir-based oxide materials and a ~8 times improvement over dealloyed Ir 25 Os 75 nanoparticles due to optimized stability and conductivity, respectively. Here, we propose that the Activity-Stability FactorASF is the key “metric” for determining the technological relevance of oxide-based anodic water electrolyzer catalysts.
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Molecular dynamics simulations and a stochastic Fokker-Planck equation based approach are used to illuminate how position-dependent solvent mobility near one or more tracer particle(s) is affected when tracer-solvent interactions are rationally modified to affect corresponding solvation structure. For tracers in a dense hard-sphere fluid, we compare two types of tracer-solvent interactions: (1) a hard-sphere-like interaction, and (2) a soft repulsion extending beyond the hard core designed via statistical mechanical theory to enhance tracer mobility at infinite dilution by suppressing coordination-shell structure [Carmer et al., Soft Matter 8, 4083–4089 (2012)]. For the latter case, we show that the mobility of surrounding solvent particles is also increased by addition of the soft repulsive interaction, which helps to rationalize the mechanism underlying the tracer’s enhanced diffusivity. However, if multiple tracer surfaces are in closer proximity (as at higher tracer concentrations), similar interactions that disrupt local solvation structure instead suppress the position-dependent solvent dynamics.
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Advances in machine learning provide the ability to leverage data from expensive simulations of high-energy-density experiments to significantly cut down on computational time and costs associated with the search for optimal target designs. This study presents an application of cutting-edge Bayesian optimization methods to the one-dimensional (1D) design optimization of double shell graded layer targets for inertial confinement fusion experiments. This investigation attempts to reduce hydrodynamic instabilities while retaining high yields for future NIF experiments. Machine learning methods can use predictive physics simulations to identify graded layer designs from within the vast design space that demonstrate high predicted performance, including novel designs with high uncertainty in performance that may hold unexpected promise. By applying machine learning tools to the simulation design, we map the trade-off between 1D yield and instability, specifically isolating parameter ranges, which maintain high performance while showing significantly improved Rayleigh–Taylor stability over the point design. Furthermore, the groundwork laid in this study will be a useful design tool for future NIF experiments with graded layer targets.
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We revisit a {nu}-driven r-process mechanism in the He shell of a core-collapse supernova, finding that it could succeed in early stars of metallicity Z < or approx. 10{sup -3}Z{sub {center_dot}}, at relatively low temperatures and neutron densities, producing A{approx}130 and 195 abundance peaks over {approx}10-20 s. The mechanism is sensitive to the {nu} emission model and to {nu} oscillations. We discuss the implications of an r process that could alter interpretations of abundance data from metal-poor stars, and point out the need for further calculations that include effects of the supernova shock.
The SS-HORSE method is applied to describe the scattering of nucleons by light nuclei based on calculations within the No-Core Shell Model with JISP16 and Daejeon16 NN interactions. The resonant states in {sup 5}He, {sup 5}Li, and {sup 7}He nuclei have been investigated. The SS-HORSE method generalized to the case of the democratic decay is also applied to study a four-neutron system (tetraneutron). The calculations with JISP16 and Daejeon16 and with chiral NN interactions indicate the existence of a rather narrow low-energy tetraneutron resonance.
Analysis of thin orthotropic shells of revolution subjected to unsymmetric loading - Vol. 1