Liquid compressibility effects during the collapse of a single cavitating bubble

The effect of liquid compressibility on the dynamics of a single, spherical cavitating bubble is studied. While it is known that compressibility damps the amplitude of bubble rebounds, the extent to which this effect is accurately captured by weakly compressible versions of the Rayleigh–Plesset equation is unclear. To clarify this issue, partial differential equations governing conservation of mass, momentum, and energy are numerically solved both inside the bubble and in the surrounding compressible liquid. Radiated pressure waves originating at the unsteady bubble interface are directly captured. Results obtained with Rayleigh–Plesset type equations accounting for compressibility effects, proposed by Keller and Miksis [J. Acoust. Soc. Am. 68, 628–633 (1980)], Gilmore, and Tomita and Shima [Bull. JSME 20, 1453–1460 (1977)], are compared with those resulting from the full model. For strong collapses, the solution of the latter reveals that an important part of the energy concentrated during the collapse is used to generate an outgoing pressure wave. For the examples considered in this research, peak pressures are larger than those predicted by Rayleigh–Plesset type equations, whereas the amplitudes of the rebounds are smaller

Simulation of low-speed buoyant flows with a stabilized compressible/incompressible formulation: the Full Navier–Stokes approach versus the Boussinesq model

This paper compares two strategies to compute buoyancy-driven flows using stabilized methods. Both formulations are based on a unified approach for solving compressible and incompressible flows, which solves the continuity, momentum, and total energy equations in a coupled entropy-consistent way. The first approach introduces the variable density thermodynamics of the liquid or gas without any artificial buoyancy terms, i.e., without applying any approximate models into the Navier–Stokes equations. Furthermore, this formulation holds for flows driven by high temperature differences. Further advantages of this formulation are seen in the fact that it conserves the total energy and it lacks the incompressibility inconsistencies due to volume changes induced by temperature variations. The second strategy uses the Boussinesq approximation to account for temperature-driven forces. This method models the thermal terms in the momentum equation through a temperature-dependent nonlinear source term. Computer examples show that the thermodynamic approach, which does not introduce any artificial terms into the Navier–Stokes equations, is conceptually simpler and, with the incompressible stabilization matrix, attains similar residual convergence with iteration count to methods based on the Boussinesq approximation. For the Boussinesq model, the SUPG and SGS methods are compared, displaying very similar computational behavior. Finally, the VMS a posteriori error estimator is applied to adapt the mesh, helping to achieve better accuracy for the same number of degrees of freedom

A posteriori pointwise error computation for 2-D transport equations based on the variational multiscale method

This article presents a general framework to estimate the pointwise error of linear partial differential equations. The error estimator is based on the variational multiscale theory, in which the error is decomposed in two components according to the nature of the residuals: element interior residuals and inter-element jumps. The relationship between the residuals (coarse scales) and the error components (fine scales) is established, yielding to a very simple model. In particular, the pointwise error is modeled as a linear combination of bubble functions and Green’s functions. If residual-free bubbles and the classical Green’s function are employed, the technology leads to an exact explicit method for the pointwise error. If bubble functions and free-space Green’s functions are employed, then a local projection problem must be solved within each element and a global boundary integral equation must be solved on the domain boundary. As a consequence, this gives a model for the so-called fine-scale Green’s functions. The numerical error is studied for the standard Galerkin and SUPG methods with application to the heat equation, the reaction–diffusion equation and the convection–diffusion equation. Numerical results show that stabilized methods minimize the propagation of pollution errors, which stay mostly locally

Genomic Features Of A Bumble Bee Symbiont Reflect Its Host Environment

Here, we report the genome of one gammaproteobacterial member of the gut microbiota, for which we propose the name >Candidatus Schmidhempelia bombi,> that was inadvertently sequenced alongside the genome of its host, the bumble bee, Bombus impatiens. This symbiont is a member of the recently described bacterial order Orbales, which has been collected from the guts of diverse insect species; however, >Ca. Schmidhempelia> has been identified exclusively with bumble bees. Metabolic reconstruction reveals that >Ca. Schmidhempelia> lacks many genes for a functioning NADH dehydrogenase I, all genes for the high-oxygen cytochrome o, and most genes in the tricarboxylic acid (TCA) cycle. >Ca. Schmidhempelia> has retained NADH dehydrogenase II, the low-oxygen specific cytochrome bd, anaerobic nitrate respiration, mixed-acid fermentation pathways, and citrate fermentation, which may be important for survival in low-oxygen or anaerobic environments found in the bee hindgut. Additionally, a type 6 secretion system, a Flp pilus, and many antibiotic/multidrug transporters suggest complex interactions with its host and other gut commensals or pathogens. This genome has signatures of reduction (2.0 megabase pairs) and rearrangement, as previously observed for genomes of host-associated bacteria. A survey of wild and laboratory B. impatiens revealed that >Ca. Schmidhempelia> is present in 90% of individuals and, therefore, may provide benefits to its host.Center for Insect Science (University of Arizona)National Science Foundation NSF 1046153NIH Director's Pioneer 1DP1OD006416-01NIH R01-HG006677Swiss National Science Foundation 140157, 147881Integrative Biolog

Bulk-driven non-equilibrium phase transitions in a mesoscopic ring

We study a periodic one-dimensional exclusion process composed of a driven and a diffusive part. In a mesoscopic limit where both dynamics compete we identify bulk-driven phase transitions. We employ mean-field theory complemented by Monte-Carlo simulations to characterize the emerging non-equilibrium steady states. Monte-Carlo simulations reveal interesting correlation effects that we explain phenomenologically.Comment: 4 pages, 3 figure

Quantum control of spin-correlations in ultracold lattice gases

We demonstrate that it is possible to prepare a lattice gas of ultracold atoms with a desired non-classical spin-correlation function using atom-light interaction of the kind routinely employed in quantum spin polarization spectroscopy. Our method is based on quantum non-demolition (QND) measurement and feedback, and allows in particular to create on demand exponentially or algebraically decaying correlations, as well as a certain degree of multi-partite entanglement.Comment: 2 figure

Enhanced photoluminescence emission from two-dimensional silicon photonic crystal nanocavities

We present a temperature dependent photoluminescence study of silicon optical nanocavities formed by introducing point defects into two-dimensional photonic crystals. In addition to the prominent TO phonon assisted transition from crystalline silicon at ~1.10 eV we observe a broad defect band luminescence from ~1.05-1.09 eV. Spatially resolved spectroscopy demonstrates that this defect band is present only in the region where air-holes have been etched during the fabrication process. Detectable emission from the cavity mode persists up to room-temperature, in strong contrast the background emission vanishes for T > 150 K. An Ahrrenius type analysis of the temperature dependence of the luminescence signal recorded either in-resonance with the cavity mode, or weakly detuned, suggests that the higher temperature stability may arise from an enhanced internal quantum efficiency due to the Purcell-effect

Dephasing of quantum dot exciton polaritons in electrically tunable nanocavities

We experimentally and theoretically investigate dephasing of zero dimensional microcavity polaritons in electrically tunable single dot photonic crystal nanocavities. Such devices allow us to alter the dot-cavity detuning in-situ and to directly probe the influence on the emission spectrum of varying the incoherent excitation level and the lattice temperature. By comparing our results with theory we obtain the polariton dephasing rate and clarify its dependence on optical excitation power and lattice temperature. For low excitation levels we observe a linear temperature dependence, indicative of phonon mediated polariton dephasing. At higher excitation levels, excitation induced dephasing is observed due to coupling to the solid-state environment. The results provide new information on coherence properties of quantum dot microcavity polaritons.Comment: Figure 2, panel (b) changed to logarithmic + linear scal

High-Dimensional Bayesian Optimisation with Large-Scale Constraints -- An Application to Aeroelastic Tailoring

Design optimisation potentially leads to lightweight aircraft structures with lower environmental impact. Due to the high number of design variables and constraints, these problems are ordinarily solved using gradient-based optimisation methods, leading to a local solution in the design space while the global space is neglected. Bayesian Optimisation is a promising path towards sample-efficient, global optimisation based on probabilistic surrogate models. While Bayesian optimisation methods have demonstrated their strength for problems with a low number of design variables, the scalability to high-dimensional problems while incorporating large-scale constraints is still lacking. Especially in aeroelastic tailoring where directional stiffness properties are embodied into the structural design of aircraft, to control aeroelastic deformations and to increase the aerodynamic and structural performance, the safe operation of the system needs to be ensured by involving constraints resulting from different analysis disciplines. Hence, a global design space search becomes even more challenging. The present study attempts to tackle the problem by using high-dimensional Bayesian Optimisation in combination with a dimensionality reduction approach to solve the optimisation problem occurring in aeroelastic tailoring, presenting a novel approach for high-dimensional problems with large-scale constraints. Experiments on well-known benchmark cases with black-box constraints show that the proposed approach can incorporate large-scale constraints.Comment: Conference paper submitted to AIAA Scitech 2024 Foru