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At least 109 records · Page 6

A finite difference treatment of Stokes-type flows: Preliminary report

The equations Laplacian operator omega = 0, (1.1a) and omega = Laplacian operator Chi, (1.1b) describe, in suitable units, 2-D Stokes flow of an incompressible fluid occupying a domain D in which omega is the vorticity and Chi is the stream function. The flow is uniquely determined by specifying the velocity on the boundary B of D, a condition which leads to specifying the stream function Chi and its normal derivative Chi sub n on B. A mathematically similar problem arises in describing the equilibrium of a flat plate in structural mechanics where a related 1-D problem by finite difference or finite element methods is to introduce effective methods for imposing the boundary conditions through which (1.1a) is coupled to (1.1b). These models thus provide a simple starting point for examining the general treatment of boundary conditions for more general time dependent Navier-Stokes incompressible flows. For the purpose of discussion it is assumed that D is a square domain. A standard finite difference method to solve (1.1) is to introduce a uniform grid and then use standard five point finite difference operators to express each equation in (1.1). At any point on the boundary B a value of Chi is specified by the boundary conditions but a value of omega at the same boundary mesh point will also be required to complete the computation. Methods are discussed which overcome the difficulty in solving these problems.

Rose, M. E.↗

Full Multigrid Flow Solver

FMG3D (full multigrid 3 dimensions) is a pilot computer program that solves equations of fluid flow using a finite difference representation on a structured grid. Infrastructure exists for three dimensions but the current implementation treats only two dimensions. Written in Fortran 90, FMG3D takes advantage of the recursive subroutine feature, dynamic memory allocation, and structured-programming constructs of that language. FMG3D supports multi-block grids with three types of block-to-block interfaces: periodic, C-zero, and C-infinity. For all three types, grid points must match at interfaces. For periodic and C-infinity types, derivatives of grid metrics must be continuous at interfaces. The available equation sets are as follows: scalar elliptic equations, scalar convection equations, and the pressure-Poisson formulation of the Navier-Stokes equations for an incompressible fluid. All the equation sets are implemented with nonzero forcing functions to enable the use of user-specified solutions to assist in verification and validation. The equations are solved with a full multigrid scheme using a full approximation scheme to converge the solution on each succeeding grid level. Restriction to the next coarser mesh uses direct injection for variables and full weighting for residual quantities; prolongation of the coarse grid correction from the coarse mesh to the fine mesh uses bilinear interpolation; and prolongation of the coarse grid solution uses bicubic interpolation.

Mineck, Raymond E.↗

Fluid Physics in a Fluctuating Acceleration Environment

Our program of research aims at developing a stochastic description of the residual acceleration field onboard spacecraft (g-jitter) to describe in quantitative detail its effect on fluid motion. Our main premise is that such a statistical description is necessary in those cases in which the characteristic time scales of the process under investigation are long compared with the correlation time of g-jitter. Although a clear separation between time scales makes this approach feasible, there remain several difficulties of practical nature: (i), g-jitter time series are not statistically stationary but rather show definite dependences on factors such as active or rest crew periods; (ii), it is very difficult to extract reliably the low frequency range of the power spectrum of the acceleration field. This range controls the magnitude of diffusive processes; and (iii), models used to date are Gaussian, but there is evidence that large amplitude disturbances occur much more frequently than a Gaussian distribution would predict. The lack of stationarity does not constitute a severe limitation in practice, since the intensity of the stochastic components changes very slowly during space missions (perhaps over times of the order of hours). A separate analysis of large amplitude disturbances has not been undertaken yet, but it does not seem difficult a priori to devise models that may describe this range better than a Gaussian distribution. The effect of low frequency components, on the other hand, is more difficult to ascertain, partly due to the difficulty associated with measuring them, and partly because they may be indistinguishable from slowly changing averages. This latter effect is further complicated by the lack of statistical stationarity of the time series. Recent work has focused on the effect of stochastic modulation on the onset of oscillatory instabilities as an example of resonant interaction between the driving acceleration and normal modes of the system, and on cavity flow as an example of how an oscillatory response under periodic driving becomes diffusive if the forcing is random instead. This paper describes three different topics that illustrate behavior that is peculiar to a stochastic acceleration field. In the first case, we show that g-jitter can induce effective attractive or repulsive forces between a pair of spherical particles that are suspended in an incompressible fluid of different density provided that the momentum diffusion length is larger than the interparticle separation (as in the case in most colloidal suspensions). Second, a stochastic modulation of the control parameter in the vicinity of a pitchfork or supercritical bifurcation is known not to affect the location of the threshold. We show, however, that resonance between the modulation and linearly stable modes close to onset can lead to a shift in threshold. Finally, we discuss the classical problem of vorticity diffusion away from a plane boundary that is being vibrated along its own plane. Periodic motion with zero average vorticity production results in an exponential decay of the vorticity away from the boundary. Random vibration, on the other hand, results in power law decay away from the boundary even if vorticity production averages to zero.

Drolet, Francois↗

Butterfly valve performance factors using the multiphysics object oriented simulation environment

Butterfly valves are typically used in nuclear reactors to control incompressible fluid flow with high inlet velocities. Performance factors for butterfly valves include the pressure drop across the valve and the loss coefficient from which hydrodynamic torque and flow coefficients can be computed. This work explores a computational fluid dynamics approach for butterfly valve performance factors using the open-source Multiphysics Object Oriented Simulation Environment (MOOSE) framework. While MOOSE is often used in the nuclear energy modeling and simulation community for simulations ranging from fuel characterization to heat pipe simulation, this work employs the MOOSE open-source Navier–Stokes solver capability for simulating butterfly valve performance factors and compares those to experimentally measured results from the Advanced Test Reactor at Idaho National Laboratory at Reynolds numbers in the order of 10 6 for the partially opened configuration. The MOOSE framework results are compared against experimentally measured butterfly valve performance factors across five valve opening angles using meshes with order 10 4 – 10 5 elements. This validation serves to enable MOOSE-based multiphysics simulations incorporating the open-source Navier–Stokes module.

97 - MATHEMATICS AND COMPUTING↗

Liquid Sorption-Enhanced Haber–Bosch Process

The use of a liquid sorbent in a traditional Haber-Bosch process enables significant improvements in energy efficiency and potential cost savings for arguably the most important chemical process on the planet. The approach presented in this report employs an incompressible liquid sorbent that absorbs and releases ammonia (NH 3 ) under specific conditions. To achieve this, we investigate reactions of ammonia and pure phosphoric acid (H 3 PO 4 , PA), which rapidly neutralize to form an equilibrated solution of monoammonium phosphate (MAP) and diammonium phosphate (DAP) that functions as a reversible and regenerable sorbent. Through intimate contact of the gas-phase Haber-Bosch reaction mixture with this liquid absorbent, complete equilibrium uptake may be achieved in an appropriately sized separator, and facile separation occurs through the use of independent liquid and gas phases. Following depressurization and release of the ammonia product, only the incompressible fluid needs to be repressurized and returned to the reactor. This study documents proof-of-concept absorption and desorption experiments carried out in 75 mL batch reactors, predominantly charged with precise MAP and DAP mixtures that equilibrate at process-relevant temperatures and pressures. We then assemble the first thermodynamic relationships that underlie this advantaged separation strategy, validated by reactive force field (ReaxFF) interatomic potential simulations, and benchmarked with traditional separation routes via process modeling and technoeconomic analysis. The scale of energy consumption in the century-old Haber-Bosch process is massive, and the elegant liquid sorption approach reported here offers opportunities to enhance its energy efficiency for the next frontier of ammonia synthesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Optical neural engine for solving scientific partial differential equations

Abstract Solving partial differential equations (PDEs) is the cornerstone of scientific research and development. Data-driven machine learning (ML) approaches are emerging to accelerate time-consuming and computation-intensive numerical simulations of PDEs. Although optical systems offer high-throughput and energy-efficient ML hardware, their demonstration for solving PDEs is limited. Here, we present an optical neural engine (ONE) architecture combining diffractive optical neural networks for Fourier space processing and optical crossbar structures for real space processing to solve time-dependent and time-independent PDEs in diverse disciplines, including Darcy flow equation, the magnetostatic Poisson’s equation in demagnetization, the Navier-Stokes equation in incompressible fluid, Maxwell’s equations in nanophotonic metasurfaces, and coupled PDEs in a multiphysics system. We numerically and experimentally demonstrate the capability of the ONE architecture, which not only leverages the advantages of high-performance dual-space processing for outperforming traditional PDE solvers and being comparable with state-of-the-art ML models but also can be implemented using optical computing hardware with unique features of low-energy and highly parallel constant-time processing irrespective of model scales and real-time reconfigurability for tackling multiple tasks with the same architecture. The demonstrated architecture offers a versatile and powerful platform for large-scale scientific and engineering computations.

Tang, Yingheng (ORCID:0009000153622546)↗

Thermal effects in face seals.

Incompressible fluid laminar and turbulent flow between face seal rotating parallel surfaces, considering conduction, convection and dissipation influence on thermal distribution

Sneck, H. J.↗