Assessment of Different CFD Modeling and Solving Approaches for a Supersonic Steam Ejector Simulation

The effects of different modeling and solving approaches on the simulation of a steam ejector have been investigated with the computational fluid dynamics (CFD) technique. The four most frequently used and recommended turbulence models (standard k-ε, RNG k-ε, realizable k-ε and SST k-ω), two near-wall treatments (standard wall function and enhanced wall treatment), two solvers (pressure- and density-based solvers) and two spatial discretization schemes ( the second-order upwind scheme and the quadratic upstream interpolation for convective kinematics (QUICK) of the convection term have been tested and compared for a supersonic steam ejector under the same conditions as experimental data. In total, more than 185 cases of 17 different modeling and solving approaches have been carried out in this work. The simulation results from the pressure-based solver (PBS) are slightly closer to the experimental data than those from the density-based solver (DBS) and are thus utilized in the subsequent simulations. When a high-density mesh with y+ < 1 is used, the SST k-ω model can obtain the best predictions of the maximum entrainment ratio (ER) and an adequate prediction of the critical back pressure (CBP), while the realizable k-ε model with the enhanced wall treatment can obtain the best prediction of the CBP and an adequate prediction of the ER. When the standard wall function is used with the three k-ε models, the realizable k-ε model can obtain the best predictions of the maximum ER, and the three k-ε models can gain the same CBP value. For a steam ejector with recirculation inside the diffuser, the realizable k-ε model or the enhanced wall treatment is recommended for adoption in the modeling approach. When the spatial discretization scheme of the convection term changes from a second-order upwind scheme to a QUICK scheme, the effect can be ignored for the maximum ER calculation, while only the CBP value from the standard k-ε model with the standard wall function is reduced by 2.13%. The calculation deviation of the ER between the two schemes increases with the back pressure at the unchoked flow region, especially when the standard k-ε model is adopted. The realizable k-ε model with the two wall treatments and the SST k-ω model is recommended, while the standard k-ε is more sensitive to the near-wall treatment and the spatial discretization scheme and is not recommended for an ejector simulation.

Discretized Fast–Slow Systems with Canards in Two Dimensions

We study the problem of preservation of maximal canards for time discretized fast–slow systems with canard fold points. In order to ensure such preservation, certain favorable structure-preserving properties of the discretization scheme are required. Conventional schemes do not possess such properties. We perform a detailed analysis for an unconventional discretization scheme due to Kahan. The analysis uses the blow-up method to deal with the loss of normal hyperbolicity at the canard point. We show that the structure-preserving properties of the Kahan discretization for quadratic vector fields imply a similar result as in continuous time, guaranteeing the occurrence of maximal canards between attracting and repelling slow manifolds upon variation of a bifurcation parameter. The proof is based on a Melnikov computation along an invariant separating curve, which organizes the dynamics of the map similarly to the ODE problem.

Analysis of the spectral symbol associated to discretization schemes of linear self-adjoint differential operators

Given a linear self-adjoint differential operator $$\mathscr {L}$$ L along with a discretization scheme (like Finite Differences, Finite Elements, Galerkin Isogeometric Analysis, etc.), in many numerical applications it is crucial to understand how good the (relative) approximation of the whole spectrum of the discretized operator $$\mathscr {L}\,^{(n)}$$ L ( n ) is, compared to the spectrum of the continuous operator $$\mathscr {L}$$ L . The theory of Generalized Locally Toeplitz sequences allows to compute the spectral symbol function $$\omega $$ ω associated to the discrete matrix $$\mathscr {L}\,^{(n)}$$ L ( n ) . Inspired by a recent work by T. J. R. Hughes and coauthors, we prove that the symbol $$\omega $$ ω can measure, asymptotically, the maximum spectral relative error $$\mathscr {E}\ge 0$$ E ≥ 0 . It measures how the scheme is far from a good relative approximation of the whole spectrum of $$\mathscr {L}$$ L , and it suggests a suitable (possibly non-uniform) grid such that, if coupled to an increasing refinement of the order of accuracy of the scheme, guarantees $$\mathscr {E}=0$$ E = 0 .

Rearrangement Algorithm in Risk Aggregation

Sometimes there’s no closed-form analytical solutions for the risk measure of aggregate losses representing, say, a company’s losses in each country or city it operates in, a portfolio of losses subdivided by investment, or claims made by clients to an insurance company. Assuming there’s enough data to assign a distribution to those losses, we examine the Rearrangement Algorithm’s ability to numerically compute the Expected Shortfall and Exponential Premium Principle/Entropic Risk Measure of aggregate losses. A more efficient discretization scheme is introduced and the algorithm is extended to the Entropic Risk Measure which turns out to have a smaller uncertainty spread than the Expected Shortfall at least for the cases that we examined.

Rearrangement Algorithm in Risk Aggregation

Sometimes there’s no closed-form analytical solutions for the risk measure of aggregate losses representing, say, a company’s losses in each country or city it operates in, a portfolio of losses subdivided by investment, or claims made by clients to an insurance company. Assuming there’s enough data to assign a distribution to those losses, we examine the Rearrangement Algorithm’s ability to numerically compute the Expected Shortfall and Exponential Premium Principle/Entropic Risk Measure of aggregate losses. A more efficient discretization scheme is introduced and the algorithm is extended to the Entropic Risk Measure which turns out to have a smaller uncertainty spread than the Expected Shortfall at least for the cases that we examined.

A numerical fitting procedure for the embedded atom method interatomic potential and a bridged finite element-molecular dynamics method for large atomic systems

This thesis presents a powerful numerical fitting procedure for generating Embedded Atom Method (EAM) inter-atomic potentials for pure Face Centred Cubic (FCC) and Body Centred Cubic (BCC) metals. The numerical fitting procedure involves assuming a reasonable parameterized form for a portion of the EAM potential, and then fitting the remaining portion to select thermal and elastic properties of the metal. Molecular Dynamics (MD) simulation is used to effect the fitting procedure. The procedure is used to generate an EAM potential for copper, an FCC metal. This resulting EAM potential is used to conduct MD simulations of perfect copper crystals containing voids of different geometries. Following this, a bridged Finite Element-Molecular Dynamics (FE-MD) method is presented, which can be used to simulate large atomic systems much more efficiently than MD simulation alone. The method implements a novel element discretization scheme proposed by the author that is so general that it can be applied to any system of objects interacting with each other via any potential (simple or complex, EAM or otherwise). This bridged FE-MD method is used to reanalyze the voids in the copper crystal lattice. The resulting virial stress increment patterns are found to agree remarkably with the earlier MD simulation results. Furthermore, the bridged FE-MD method is much quicker than the pure MD simulation. These two facts prove the power and usefulness of the bridged FE-MD method, and validate the proposed element discretization scheme

A numerical fitting procedure for the embedded atom method interatomic potential and a bridged finite element-molecular dynamics method for large atomic systems

This thesis presents a powerful numerical fitting procedure for generating Embedded Atom Method (EAM) inter-atomic potentials for pure Face Centred Cubic (FCC) and Body Centred Cubic (BCC) metals. The numerical fitting procedure involves assuming a reasonable parameterized form for a portion of the EAM potential, and then fitting the remaining portion to select thermal and elastic properties of the metal. Molecular Dynamics (MD) simulation is used to effect the fitting procedure. The procedure is used to generate an EAM potential for copper, an FCC metal. This resulting EAM potential is used to conduct MD simulations of perfect copper crystals containing voids of different geometries. Following this, a bridged Finite Element-Molecular Dynamics (FE-MD) method is presented, which can be used to simulate large atomic systems much more efficiently than MD simulation alone. The method implements a novel element discretization scheme proposed by the author that is so general that it can be applied to any system of objects interacting with each other via any potential (simple or complex, EAM or otherwise). This bridged FE-MD method is used to reanalyze the voids in the copper crystal lattice. The resulting virial stress increment patterns are found to agree remarkably with the earlier MD simulation results. Furthermore, the bridged FE-MD method is much quicker than the pure MD simulation. These two facts prove the power and usefulness of the bridged FE-MD method, and validate the proposed element discretization scheme