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At least 55 records · Page 3

Influence of drag coefficient equations on particle motion calculations

An important phase of laser velocimetry investigations in gas flow fields is an analysis of the particle motion in the gas. The present paper examines three important aspects of particle motion calculations. A comparison of various drag coefficient equations with available experimental sphere drag data is made to determine the relative accuracy of the various empirical expressions available. Then, the most accurate drag coefficient equation is used to determine the limitations of Stokes drag equation for calculating relaxation lengths behind normal shocks, and percent velocity lags in one-dimensional constant velocity gradient regions. Finally, a two-dimensional constant velocity gradient gas flow field is examined to determine the importance of the coupling between the governing equations for the components of particle velocity.

Walsh, M. J.↗

Drag on the Lageos satellite

The drag data on the Lageos satellite collected between 1976 and 1987 are analyzed, and the cause of fluctuations observed at times when the orbit intersects the earth's shadow is investigated. The average drag on the Lageos consists of three types of drag: the Yarkovsky thermal drag, which accounts for about 70 percent of the observed drag; the neutral particle drug, accounting for about 14 percent of the drag for a hydrogen number density of 5 x 10 to the 9th/cu m; and the charged particle drag, which accounts for 12 percent of average drag at a number density of 3 x 10 to the 9th and a temperature of 5000 K in the plasmasphere for a satellite potential of -1 V. The observed drag agrees with the particle environment at the Lageos altitude and the drag models. However, the fluctuations in Lageos's along-track acceleration when the orbit intersects the earth's shadow are still not well understood.

Rubincam, David Parry↗

An Investigation of the Effects of Volume Fraction on Drag Coefficient of Non-Spherical Particles Using PR-DNS

Prediction of the drag coefficient is required in gas-particle multiphase flow modeling and simulation. Experimental data and correlations on the fixed-bed system of spherical particles with high volume fractions for various possible arrangements are available in the literature. However, the effect of volume fraction on the drag coefficient of non-spherical particles is not well studied. In solving the momentum equation, the volume fraction plays a vital role in determining the flow resistances. In this paper, we study the impact of volume fraction in the range of 0.069 to 0.65 on the drag coefficient using the computational fluid dynamics (CFD) simulation of air for Reynold number in the range of 10 to 10000 using particle resolved direct numerical solution (PR-DNS). Regular non-spherical particles such as a cube, tetrahedron, and spheroids are used in this study since their single particle’s drag coefficient data are available in the literature for comparison. For this work, the simulations are carried out in the Ansys Fluent using polyhedral mesh, which consumes significantly less computational time and power. The study showed the sphericity and volume fraction have significant impact on the bed pressure drop and average drag coefficient of the particles in the bed especially in high Reynolds number regime. The bed of the spheroid experiences the lowest drag being the most streamlined particle, and the particles with the edges result in a large drag coefficient due to flow separation at the discontinuity. The vector plots verify this behavior where large wake regions are observed behind the tetrahedron particle.

Mahyawansi, Pratik↗

Modal analysis of the behavior of inertial particles in turbulence subjected to Stokes drag

The clustering of small heavy inertial particles subjected to Stokes drag in turbulence, which is the concern of present study, is known to be minimal at small and large Stokes number and substantial at St = $\textit{O}$(1). This nonmonotonic trend, which has been shown computationally and experimentally, is yet to be explained analytically. In this study, we obtain an analytical expression for the Lyapunov exponents that quantitatively predicts this trend. The sum of the exponents, which is the normalized rate of change of the signed volume of a small cloud of particles, is correctly predicted to be negative and positive at small and large Stokes numbers, respectively, asymptoting to $\textit{τQ}$ as $\textit{τ}$ → 0 and $τ^{–1/2}|Q|^{1/4}$ as $\textit{τ} → ∞$, where $\textit{τ}$ is the particle relaxation time and $\textit{Q(τ)}$ is the difference between the norm of the rotation- and strain-rate tensors computed along the particle trajectory, which remains negative at all $\textit{τ}$ in turbulent flows. Additionally, the trajectory crossing is predicted only in hyperbolic flows where Q < 0 for sufficiently inertial particles with a $\textit{τ}$ that scales with $|Q|^{–1/2}$. Following the onset of crossovers, a transition from clustering to dispersion is predicted correctly. We show these behaviors are not unique to three-dimensional isotropic turbulence and can be reproduced closely by a one-dimensional mono-harmonic flow, which appears as a fundamental canonical problem in the study of particle clustering. Analysis of this one-dimensional canonical flow shows that the rate of clustering, quantified as the product of the Lyapunov exponent and particle relaxation time, is bounded by –1/2, behaving with extreme nonlinearity in the hyperbolic flows and always remaining positive in the elliptic flows. Finally, this model problem also confirms that dispersion in a hyperbolic flow will occur only if particles' trajectory cross. These findings, which stem from our analysis, are corroborated by the direct numerical simulations.

42 ENGINEERING↗

Viscous drag reduction in boundary layers

The present volume discusses the development status of stability theory for laminar flow control design, applied aspects of laminar-flow technology, transition delays using compliant walls, the application of CFD to skin friction drag-reduction, active-wave control of boundary-layer transitions, and such passive turbulent-drag reduction methods as outer-layer manipulators and complex-curvature concepts. Also treated are such active turbulent drag-reduction technique applications as those pertinent to MHD flow drag reduction, as well as drag reduction in liquid boundary layers by gas injection, drag reduction by means of polymers and surfactants, drag reduction by particle addition, viscous drag reduction via surface mass injection, and interactive wall-turbulence control.

Bushnell, Dennis M.↗

Calculation of particle dynamics effects on laser velocimeter data

In order to analytically assess the effects of particle dynamics on laser velocimeter measurements, the particle response to the fluid in which it is entrained must be modeled. The equation of particle motion derived at Arnold Engineering and Development Center (AEDC), is used to model the motion of the particle. The equation is derived from the Navier-Stokes equation under the assumption of unsteady Stokes flow. It should be noted that the Stokes flow eliminates the need for a far field boundary condition, and hence eliminates any normal (lift) forces. To extend the equation to higher particle slip velocities, the Stokes drag is replaced with the particle drag law, modified to include heat transfer effects. The drag coefficient accounts for inertial, rarefaction, compressibility, shape, and heat transfer effects.

Nichols, R. H.↗

Radiation pressure and Poynting-Robertson drag for small spherical particles

Robertson's expression for the velocity-dependent effect of solar radiation on the motion of small particles is difficult because of its dependence on relativistic considerations, and it is also deficient in that it assumes perfectly absorbing particles. The present paper gives a heuristic derivation of the Poynting-Robertson effect. Robertson's expression for perfectly absorbing particles is obtained but on a much simpler physical basis, and an expression is also obtained for a particle that in general scatters, transmits, and absorbs light. Some numerical results on the solar radiation forces felt by small particles of cosmochemically important compositions are given.

Soter, S.↗

Numerical Calculation of the Drag Force Acting on an Insoluble Particle Moving in Front of a Solidifying Interface

The distribution of insoluble particles in a metal casting depends primarily on the interaction of the particles with the solid/liquid interface (SLI) during the solidification process. Whether a particle will be engulfed or continuously pushed by SLI is essentially determined by the balance of forces acting on the particle. An important component of this force balance is the drag force generated by the particle motion in front of the SLI. Previously developed mathematical models for particle/SLI interaction made use of steady-state solutions of this force provided by the lubrication theory. However, our numerical model based on the SLI tracking approach shows that not only the steady-state approach is inappropriate to model the interaction process but also that even at steady-state the theoretical solution underestimates the drag force. A regression analysis of steady-state numerical solutions for cylindrical particles moving normal to a flat SLI gave a relationship of the form F(sub d) (exp num) = (square root of 3) pi eta V(sub p)((R(sub p) / d) (exp 10 gamma/3)) as compared to the theoretical solution F(sub d) (exp theor) = 3 X (square root of 2) pi eta V(sub p)((R(sub p) / d) (exp 3/2)) where F(sub d) is the drag force, eta is the dynamic viscosity of the fluid, V(sub p) is the particle velocity, R(sub p) is the particle radius, gamma is Euler's constant (gamma is approximately equal to 0.577), and d is the width of the gap between the particle and the SLI. Model validation as well as the influence of the interface shape on the value of F(sub d) will also be discussed.

Catalina, Adrian V.↗

Numerical Calculation of the Drag Force Acting on a Solid Particle Pushed by a Solid/Liquid Interface

The distribution of insoluble particles in a metal casting depends primarily on the interaction of the particles with the solid/liquid interface (SLI) during the solidification process. The balance of the forces acting on the particle essentially determines whether a particle will be engulfed or pushed by the SLI. An important component of this force balance is the drag force generated by the particle motion in front of the SLI. Previously developed mathematical models for particle/SLI interaction made use of steady-state solutions of this force provided by the lubrication theory. However, our numerical model based on the SLI tracking approach shows that the steady-state approach is inappropriate to model the interaction process and that at steady-state the theoretical solution underestimates the drag force. It was found that regression analysis of steady-state numerical solutions for cylindrical particles moving normal to a flat SLI gives a relationship of the form: Abstract The distribution of insoluble particles in a metal casting depends primarily on the interaction of the particles with the solid/liquid interface (SLI) during the solidification process. The balance of the forces acting on the particle essentially determines whether a particle will be engulfed or pushed by the SLI. An important component of this force balance is the drag force generated by the particle motion in front of the SLI. Previously developed mathematical models for particle/SLI interaction made use of steady-state solutions of this force provided by the lubrication theory. However, our numerical model based on the SLI tracking approach shows that the steady-state approach is inappropriate to model the interaction process and that at steady-state the theoretical solution underestimates the drag force. It was found that regression analysis of steady-state numerical solutions for cylindrical particles moving normal to a flat SLI gives a relationship of the form: F(sub D, sup num) =sqoare root of 3(pi)(eta)V(sub p)(R(sub p)/d)(sup 10(gamma)/3). This is to compared to the solution provided by the lubrication theory: F(sub D), sup theor) = 3 square root of 2(pi)(eta)V(sub p)(R(sub p)/d)(sub 3/2), where F(sub D) is the drag force, eta is the dynamic viscosity of the fluid, V(sub p) is the particle velocity, R(sub p) is the particle radius, gamma is Euler's constant (gamma approx. = 0.577), and d is the width of the gap between the particle and the SLI. The domain on which the equations proposed by the lubrication theory are relevant is clearly identified in the paper. The numerical model was then validated against the classical lubrication theory within the domain of its validity.

Catalina, Adrian V.↗

Theory of Dust Voids in Plasmas

Dusty plasmas in a gas discharge often feature a stable void, i.e., a dust-free region inside the dust cloud. This occurs under conditions relevant to both plasma processing discharges and plasma crystal experiments. The void results from a balance of the electrostatic and ion drag forces on a dust particle. The ion drag force is driven by a flow of ions outward from an ionization source and toward the surrounding dust cloud, which has a negative space charge. In equilibrium the force balance for dust particles requires that the boundary with the dust cloud be sharp, provided that the particles are cold and monodispersive. Numerical solutions of the one-dimensional nonlinear fluid equations are carried out including dust charging and dust-neutral collisions, but not ion-neutral collisions. The regions of parameter space that allow stable void equilibria are identified. There is a minimum ionization rate that can sustain a void. Spatial profiles of plasma parameters in the void are reported. In the absence of ion-neutral collisions, the ion flow enters the dust cloud's edge at Mach number M = 1. Phase diagrams for expanding or contracting voids reveal a stationary point corresponding to a single stable equilibrium void size, provided the ionization rate is constant. Large voids contract and small voids expand until they attain this stationary void size. On the other hand, if the ionization rate is not constant, the void size can oscillate. Results are compared to recent laboratory and microgravity experiments.

Goree, J.↗

Development of a Deep Learning Model for Predicting the Drag Coefficients of Spherical and Non-Spherical Particles,

There is yet to be a well-established drag model for non-spherical particles required in a particle-laden flow that could cover a wide range of sphericities. This talk will explore the development of a general drag model for non-spherical particles by applying deep learning using available experimental data available in the literature. The integration of several raw experimental measurements from different sources and research directions allows the training of robust Artificial Intelligence and Machine Learning (ML) models. Neural networks are an ML approach inspired by the inner biological workings of the brain. This work aims to develop a Deep Neural Network (DNN) that predicts drag coefficient values with the ability to adapt appropriately to unseen data. Given the limited number of data points available and the variance found within the data collected from various sources, challenges may arise when looking to train the model. Our study tests and implements various model regularization techniques and assesses different loss and activation functions for the proposed DNN. The proposed model considers a broader range of features other than sphericity and Reynold number. These features include density ratio, solid volume fraction, lengthwise and crosswise sphericity, and more. Furthermore, we present the features that play a significant role in predicting different drag coefficients through feature importance. Within the investigated parameter ranges in this study, the following conclusions can be achieved and summarized below: • An improved drag coefficient model can be developed by considering more features such as, aspect ratio, lengthwise sphericity, crosswise sphericity, and density ratio. • DNN model can predict better results compared to traditional methods using MAE metric. • The proposed model addresses data challenges such as limited data and extreme data points through expanded feature-set and regularization. • Three major features that mostly affect the drag coefficient were identified from a feature importance analysis.

Presa-Reyes, Maria↗