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The occurrence of oil whirl instability in rigid and flexible rotor systems was investigated. The effect of various bearing parameters on the oil whirl frequency and amplitude of rigid and flexible shafts supported on fluid film bearings was also studied.
Inward and downflow motions below the photosphere are considered to be a means of cooling and powering sunspot dynamics. Parker's superadiabatic effect is examined with attention focused on the energetics involved in ionization advection. The current analysis enhances Parker's mechanism by allowing for a 2 m/s downflow velocity at 2000 km depth to significantly reduce the photospheric irradiance to near umbral intensities. Similarities between sunspots and terrestrial hurricanes are noted, and it was found that ionization energy plays the same role in sunspots as latent energy plays in terrestrial weather systems. Based on the hypothesis that magnetic fields are important in organizing the motions on the sun, some understanding is provided of: (1) the instability which drives the cooling mechanism for sunspots, (2) the low latitude appearance of sunspots, (3) active region development with faculae following sunspot growth, (4) the role of the fluid in maintaining the magnetic field and the role of the field as a focal point for the fluid downflow, (5) the heating mechanism and structure of faculae, (6) energy balance in active regions, and (7) the behavior difference of pores and ephemeral active regions in relation to ordinary sunspots and active regions.
A method for calculating mean square velocity fluctuations, mean square temperature fluctuations, and convective flux for a turbulent rotating fluid with externally applied magnetic field is presented. A new spectral model of large scale turbulence is used which requires, as the sole ingredient, the growth rate of the instability generating the turbulence. Results are presented for the convective flux with rotation and magnetic field for a range of parameters of astrophysical interest. This new formula presented here can be viewed as an extension of the mixing length theory to include magnetic fields and rotation.
Here, the laws governing the flow of a compressible fluid through an opening in a thin wall are applied to the resistance of the air at high speeds, especially as applied to the automatic rotation of projectiles. The instability which we observe in projectiles shot into the air without being given a moment of rotation about their axis of symmetry, or without stabilizing planes, is a phenomenon of automatic rotation. It is noted that we can prevent this phenomenon of automatic rotation by bringing the center of gravity sufficiently near one end, or by fitting the projectile with stabilizing planes or a tail. The automatic rotation of projectiles is due to the suction produced by the systematic formation of vortices behind the extremity of the projectile moving with the wind.
A physical principle (more precisely, a principle that incorporates mathematical models used in physics) has been conceived as the basis of a method of generating randomness in Monte Carlo simulations. The principle eliminates the need for conventional random-number generators. The Monte Carlo simulation method is among the most powerful computational methods for solving high-dimensional problems in physics, chemistry, economics, and information processing. The Monte Carlo simulation method is especially effective for solving problems in which computational complexity increases exponentially with dimensionality. The main advantage of the Monte Carlo simulation method over other methods is that the demand on computational resources becomes independent of dimensionality. As augmented by the present principle, the Monte Carlo simulation method becomes an even more powerful computational method that is especially useful for solving problems associated with dynamics of fluids, planning, scheduling, and combinatorial optimization. The present principle is based on coupling of dynamical equations with the corresponding Liouville equation. The randomness is generated by non-Lipschitz instability of dynamics triggered and controlled by feedback from the Liouville equation. (In non-Lipschitz dynamics, the derivatives of solutions of the dynamical equations are not required to be bounded.)
A number of important physics effects on the stability of relatively high-n (n is the toroidal mode number) peeling-ballooning modes (PBMs) are investigated based on an equilibrium reconstructed from a NSTX discharge, utilizing extended magnetohydrodynamic (MHD) eigenvalue solvers. For a given toroidal mode number n, multiple branches of instabilities are computed, with the total number of unstable branches roughly linearly scaling with n. Most of the unstable branches are located in the plasma core region, but edge-localized branches, i.e., PBMs, are also identified at higher n-numbers. For the single-fluid-wise most unstable PBM with n = 19, stabilizing/destabilizing effects due to various physics beyond ideal MHD are systematically investigated. Plasma toroidal flow is found to be weakly stabilizing. Local flow shear is generally stabilizing as well, with the degree of stabilization depending on the initial growth rate (without flow shear) of the mode. The plasma resistivity can strongly destabilize the PBM within the single-fluid framework. Anisotropic thermal transport, strong parallel sound wave damping, as well as two-fluid effects are all stabilizing to the mode. In particular, diamagnetic stabilization (within the two-fluid model) is found to be very strong for this mode.
Theoretical and numerical works in atmospheric turbulence have used the Navier-Stokes fluid equations exclusively for describing large-scale motions. Controversy over the existence of an average temperature gradient for the very large eddies in the atmosphere suggested that a new theoretical basis for describing large-scale turbulence was necessary. A new soliton formalism as a fluid analogue that generalizes the Schrodinger equation and the Zakharov equations has been developed. This formalism, processing all the nonlinearities including those from modulation provided by the density fluctuations and from convection due to the emission of finite sound waves by velocity fluctuations, treats large-scale turbulence as coalescing and colliding solitons. The new soliton system describes large-scale instabilities more explicitly than the Navier-Stokes system because it has a nonlinearity of the gradient type, while the Navier-Stokes has a nonlinearity of the non-gradient type. The forced Schrodinger equation for strong fluctuations describes the micro-hydrodynamical state of soliton turbulence and is valid for large-scale turbulence in fluids and plasmas where internal waves can interact with velocity fluctuations.
The high computational cost associated with solving for detailed chemistry poses a significant challenge for predictive computational fluid dynamics (CFD) simulations of turbulent reacting flows. While deep learning techniques have been explored to develop faster surrogate models, they often fail to integrate reliably with CFD solvers. This instability arises because traditional deep learning approaches optimize for training error without ensuring compatibility with ordinary differential equation (ODE) solvers, resulting in accumulation of errors over time. Recently, neuralODE (NODE) based approaches have been shown to be a promising technique to emulate and accelerate detailed chemistry computations. Here, in the present work, we extend this NODE framework for stiff chemical kinetics by incorporating mass conservation constraints directly into the loss function during training. This ensures that the total mass as well as the individual elemental species masses are conserved in an a-posteriori manner. Proof-of-concept studies are performed with the novel physics-constrained NODE (PC-NODE) approach for homogeneous autoignition of hydrogen-air mixture over a range of composition and thermodynamic conditions. It is demonstrated that the PC-NODE framework not only improves the physical consistency of the resulting data-driven model with respect to mass conservation criteria, but also improves training efficiency. PC-NODE is shown to achieve 2–100× speedup relative to the hydrogen-air detailed chemical mechanism depending on the type of the ODE solver (implicit or explicit) used during autoregressive inference tests. Lastly, a-posteriori studies are performed wherein the trained PC-NODE model is coupled with a CFD solver. It is shown that higher accuracy is achieved with PC-NODE relative to the purely data-driven NODE approach. Moreover, PC-NODE also exhibits robustness and generalizability to unseen initial conditions from within (interpolative capability) as well as outside (extrapolative capability) the training regime.
This special issue celebrates the scientific legacy of Dr. Malcolm J. Andrews, former Editor of the ASME Journal of Fluids Engineering (2010–2018). Malcolm devoted his career to the development and applications of computational, experimental, and analytical tools to investigate and solve diverse, complex fluid dynamics, and heat transfer problems. Malcolm’s most notable research accomplishments include: (i) contributions to innovative experiments, simulations, and theory to understand buoyancydriven turbulent mixing due to Rayleigh–Taylor instability; (ii) development of the multiphase particle-in-cell method for understanding fragmentation in spray jets, coal-water slurry, and other dense particulate flows; (iii) mixing in nano- and biomaterials in applications ranging from protein glues to carbon nanotube composites; (iv) determining dispersion in proteins to improve therapeutic drug delivery via micro-encapsulation; (v) innovative methods for storing information using nanopinned dipole magnetic vortices in superconducting materials; and (vi) modeling and design modifications for shell-and-tube heat exchangers, as well as heat transfer in rotating systems such as turbine blades. The results of his research have been published in a long series of trend-setting journal and conference papers, book chapters, and patents.
The problem of forced fluid vibrations in a partially filled spinning spherical tank is solved numerically by using the finite element method. The governing equations include Coriolis acceleration and spatially homogeneous vorticity. An exponential instability is detected in the present simulation for fill ratios below 0.5 and centrifugal acceleration to thrust ratios less than 1.7. This fictitious instability appears in the model as a result of the homogeneous vortex assumption since the free slosh equations are neutrally stable in the Liapunov sense.
Studies of the structure and evolution of slow mode shocks obtained by numerical simulation are presented. It is shown that slow shocks can be formed self-consistently and evolve slowly in time, while maintaining a well-defined structure. As fluid theory predicts, the dominant feature is a trailing magnetic wavetrain whose damping length increases with time toward the fluid limit. The behavior of the ions which are backstreaming from the shock are investigated and the stability of the upstream distributions to the types of electromagnetic ion-beam instabilities found in the earth's foreshock are examined.
Two dimensional plasma particle simulations of the evolution of large amplitude circularly polarized Alfven waves propagating parallel to the magnetic field show that the waves decay via both one- and two- dimensional parametric decay instabilities. For parameters studied, one-dimensional processes dominate the simulations, but two-dimensional decay processes, including the recently predicted filamentation instability are also observed. The daughter waves generated by the parametric decay are primarily damped by the ions, leading to ion heating. The parametric decay processes efficiently convert the ordered fluid ion motion in the Alfven wave into ion thermal energy. These processes may be important for the dissipation of Alfven waves in the solar wind, the corona and other space plasma environments. The computations were performed on the Intel Touchstone parallel supercomputer.
A substantial effort has been made to implement an enhanced aerodynamic modeling capability in the Higher-fidelity Conceptual Design and structural optimization tool. This additional capability is needed for a rapid, physics-based method of modeling advanced aircraft concepts at risk of structural failure due to dynamic aeroelastic instabilities. To adequately predict these instabilities, in particular for transonic applications, a generalized aerodynamic matching algorithm was implemented to correct the doublet-lattice model available in Nastran using solution data from a priori computational fluid dynamics anal- ysis. This new capability is demonstrated for two tube-and-wing aircraft configurations, including a Boeing 737-200 for implementation validation and the NASA D8 as a first use case. Results validate the current implementation of the aerodynamic matching utility and demonstrate the importance of using such a method for aircraft configurations featuring fuselage-wing aerodynamic interaction.
Certain hemodynamic phenomena that arise in connection with the use of artificial blood pumping devices are reviewed. Among these are: (1) Flows produced by collapsing bulbs; (2) the impedance presented by the aorta; (3) limiting velocities and instability of flow in elastic vessels; (4) effectiveness of valveless arterio-arterial pumps, and (5) wave reflection phenomena and instabilities associated with the intra-aortic balloon pump.
Long gyrostatically rotating drops bonded by surface tension are amenable to conventional bifurcation analysis and newer, computer-aided analytical methods, and therefore are useful prototypes of three-dimensional drops. A study is conducted by setting aside instability to Rayleigh's axisymmetric mode and investigating the effects of translationally symmetric (planar) disturbances. The disadvantage of employing single-coordinate representation of drop shapes close to break-up is brought out. It is shown that a family of symmetric two-lobed shapes bifurcates from the main family of perfectly cylindrical shapes when the rotation rate reaches a critical value, in accord with the linearized hydrodynamic analysis of Hocking.
An analytical technique for the prediction of the effects of rigid baffles on the stability of liquid propellant combustors is presented. This analysis employs a three dimensional combustor model characterized by a concentrated combustion source at the chamber injector and a constant Mach number nozzle. An eigenfunction-matching method is used to solve the linearized partial differential equations describing the unsteady flow field. Boundary layer corrections to this unsteady flow are used in a mechanical energy dissipation model to evaluate viscous and turbulence effects within the flow. An integral stability relationship is then employed to predict the decay rate of the oscillations. Results of this analysis agree qualitatively with experimental observations and show that sufficient dissipation exists to indicate that the proper mechanism of baffle damping is a fluid dynamic loss. The response of the dissipation model to varying baffle blade length, mean flow Mach number and oscillation amplitude is examined.
Improved labyrinth seal designs are disclosed. The present invention relates to labyrinth seal systems with selected sealing surfaces and seal geometry to optimize flow deflection and produce maximum turbulent action. Optimum seal performance is generally accomplished by providing sealing surfaces and fluid cavities formed to dissipate fluid energy as a function of the geometry of the sealing surfaces along with the position and size of the fluid cavities formed between members of the labyrinth seal system. Improved convex surfaces, annular flow reversal grooves, flow deflection blocks and rough, machined surfaces cooperate to enhance the performance of the labyrinth seal systems. For some labyrinth seal systems a mid-cavity throttle and either rigid teeth or flexible spring teeth may be included.
Magnetohydrodynamic (MHD) instabilities and runaway electrons (REs) interact in several ways, making it important to self-consistently model these interactions for accurate predictions of RE generation and the design of mitigation strategies, such as massive gas injection (MGI). Using M3D-C1 – an extended MHD code with a RE fluid model – we investigate the effects of 3-D nonlinear MHD activity, material injection, and 2-D axisymmetric vertical displacement events (VDEs) on RE evolution during disruptions on SPARC – a high-field, high-current tokamak designed to achieve a fusion gain Q > 1. Several cases, comprising different combinations of neon (Ne) and deuterium (D 2 ) injection, are considered. Here, our results demonstrate key effects that arise from the self-consistent RE + MHD coupling, such as an initial increase in RE generation due to MHD instability growth, decreased saturation energies of the m/n = 1/1 mode driving sawteeth-like activity, RE losses in stochastic magnetic fields, and subsequent RE confinement and plateau formation due to re-healing of flux surfaces. Large RE plateaus (>5 MA) are obtained with Ne-only injection (2-5 × 10 21 atoms), while combined D 2 + Ne injection (2 × 10 21 Ne atoms; 1.8 × 10 22 D 2 molecules) produces a lower RE current (<2 MA). With D 2 + Ne injection, a post thermal quench "cold" VDE terminates the RE beam, preventing a steady plateau. These simulations couple REs, 3-D MHD instabilities, MGI, and axisymmetric VDEs for the first time in SPARC disruption simulations and represent a crucial step in understanding RE generation and mitigation in high-current devices like SPARC.