Flow-aligned tensor models for suspension flows

Fang, Zhiwu; Mammoli, Andrea; Brady, John F.; Ingber, M. S.; Mondy, Lisa Ann; Graham, Alan L.

doi:10.1016/s0301-9322(01)00055-6

Cited by 87 publications

(108 citation statements)

References 29 publications

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“…A recent paper by Fang et al 7 discusses mass transport driven by gradients in the stress. Here, gradients are assumed to be small enough that their explicit contributions to the stress tensor need not be taken into account.…”

Section: Introductionmentioning

confidence: 99%

Stresses in inhomogeneous suspensions

Dhont

Briels

2002

The Journal of Chemical Physics

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A microscopic expression for the divergence of the stress tensor is derived for inhomogeneous suspensions of rigid colloidal particles of arbitrary shape. This expression is valid for arbitrary large gradients in the shear rate, concentration, and orientational order parameters. The corresponding Navier-Stokes equation is a necessary ingredient to describe phenomena like shear-banding, phase separation kinetics, and phase coexistence under shear flow conditions.

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Section: Introductionmentioning

confidence: 99%

Stresses in inhomogeneous suspensions

Dhont

Briels

2002

The Journal of Chemical Physics

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“…In this section, the solution algorithm is validated on cases for which both experimental and numerical data are available: circular Couette flow, piston-driven flow and sudden contractionexpansion flow [9,13].…”

Section: Validationmentioning

confidence: 99%

“…The suspension balance model was first introduced by Nott and Brady [11], who introduced the concept of suspension 'temperature'. Morris and Boulay [12] modified the model to take into account the effect of the normal stress difference, whereas Fang et al [13] used a flow-aligned tensor to model the normal stress difference for both diffusive flux model and suspension balance model. Experimental validation of both diffusive flux and suspension balance models is shown in References [14,15].…”

Section: Introductionmentioning

confidence: 99%

“…The solution algorithm and the finite element approach are described in Section 3. In Section 4, the approach is validated for flow problems for which experimental data are available: circular Couette flow, piston-driven flow and sudden contractionexpansion flow [9,13,17]. The ALE formulation is first compared with an Eulerian solution for the case of the piston-driven flow problem and used to solve the sudden contraction-expansion flow.…”

Section: Introductionmentioning

confidence: 99%

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Three‐dimensional free surface flow simulation of segregating dense suspensions

Ilinca

Hétu

2008

Numerical Methods in Fluids

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SUMMARYThis paper presents a 3D numerical solution algorithm for the simulation of free surface flows of dense suspensions including particle migration phenomena. Segregation of the solid phase in processes such as powder injection molding and molding of semi-solid materials affects the rheology of the mixture and therefore the filling pattern. Segregation affects also the final properties and characteristics of such molded parts as a non-uniform particles distribution leads to non-uniform shrinkage, warpage and non-uniform mechanical properties. In this paper, particle migration is modeled using the diffusion flux model of Phillips et al. (Phys. Fluids A 1992; 4:30-40) and is extended to address 3D mold filling problems. The solution algorithm is validated against flow problems for which experimental and numerical data are available: circular Couette flow, piston-driven flow and sudden contraction-expansion flow. The particle migration model is then used to simulate mold filling problems in which the piston movement in the sleeve is known to induce particle migration before the material enters the cavity. An arbitrary Lagrangian-Eulerian (ALE) formulation is developed and combined to a level-set front capturing method to simulate the piston movement and the evolution of the free surface in molding simulations. The ALE formulation is first compared with an Eulerian solution for the case of the piston-driven flow problem. The approach is then applied to injection molding problems to study the evolution of particle distributions during molding and in the final molded parts.

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“…Details of our equations, numerical method and implementation can be found in a variety of sources such as internal Sandia memoranda and peered reviewed journals [See for instance; Rao et al, 1997;Tetlow et al, 1998: Sun, 1998Romero, 1999;Rao et al, 2001a: Rao et al, 2001b, Fang et al, 2001]. …”

Section: Suspension Modelmentioning

confidence: 99%

Verification and Validation of Encapsulation Flow Models in GOMA, Version 1.1

Mondy¹,

Rao²,

Schunk³

et al. 2001

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Encapsulation is a common process used in manufacturing most non-nuclear components including: firing sets, neutron generators, trajectory sensing signal generators (TSSGs), arming, fusing and firing devices (AF&Fs), radars, programmers, connectors, and batteries. Encapsulation is used to contain high voltage, to mitigate stress and vibration and to protect against moisture. The purpose of the ASCI Encapsulation project is to develop a simulation capability that will allow us to aid in the encapsulation design process, especially for neutron generators.The introduction of an encapsulant poses many problems because of the need to balance ease of processing and properties necessary to achieve the design benefits such as tailored encapsulant properties, optimized cure schedule and reduced failure rates. Encapsulants can fail through fracture or delamination as a result of cure shrinkage, thermally induced residual stresses, voids or incomplete component embedding and particle gradients. Manufacturing design requirements include 1) maintaining uniform composition of particles in order to maintain the desired thermal 4 coefficient of expansion (CTE) and density, 2) mitigating void formation during mold fill, 3) mitigating cure and thermally induced stresses during cure and cool down, and 4) eliminating delamination and fracture due to cure shrinkage/thermal strains. The first two require modeling of the fluid phase, and it is proposed to use the finite element code GOMA to accomplish this. The latter two require modeling of the solid state; however, ideally the effects of particle distribution would be included in the calculations, and thus initial conditions would be set from GOMA predictions. These models, once they are verified and validated, will be transitioned into the SIERRA framework and the ARIA code. This will facilitate exchange of data with the solid mechanics calculations in SIERRA/ADAGIO.Changes in the encapsulation process design of the 4380 neutron generator, which is in production, must be minimal, in order to avoid delays in meeting production schedules. However, concern over the processibility of the encapsulant materials and the indications that voids were occurring have resulted in rather extensive changes to the process to date, and further changes based on sound scientific principles would not be arbitrarily ruled out. The primary driver for improved computational modeling capabilities is for the design of the upcoming 4531 neutron generator. In this generator, a completely new encapsulant material is being proposed, primarily in order to replace a carcinogenic curing agent with a more benign material. Because a new material is required, computational modeling could 1) help design the material itself, 2) aid in the design and optimization of the encapsulation process to be used with this new material, 3) determine the consequences of material and process changes and minimize any adverse effects, and 4) provide confidence in the material as it ages.A "Phenomena Identification Ranking Tab...

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Flow-aligned tensor models for suspension flows

Cited by 87 publications

References 29 publications

Stresses in inhomogeneous suspensions

Stresses in inhomogeneous suspensions

Three‐dimensional free surface flow simulation of segregating dense suspensions

Verification and Validation of Encapsulation Flow Models in GOMA, Version 1.1

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