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J. Verif. Valid. Uncert. 2018;2(4):041001-041001-13. doi:10.1115/1.4038904.

The objective of this investigation is to verify a new total Lagrangian continuum-based fluid model that can be used to solve two- and three-dimensional fluid–structure interaction problems. Large rotations and deformations experienced by the fluid can be captured effectively using the finite element (FE) absolute nodal coordinate formulation (ANCF). ANCF elements can describe arbitrarily complex fluid shapes without imposing any restriction on the amount of rotation and deformation within the finite element, ensure continuity of the time-rate of position vector gradients at the nodal points, and lead to a constant mass matrix regardless of the magnitude of the fluid displacement. Fluid inertia forces are computed, considering the change in the fluid geometry as the result of the large displacements. In order to verify the ANCF solution, the dam-break benchmark problem is solved in the two- and three-dimensional cases. The motion of the fluid free surface is recorded before and after the impact on a vertical wall placed at the end of the dam dry deck. The results are in good agreement with those obtained by other numerical methods. The results obtained in this investigation show that the number of degrees-of-freedom (DOF) required for ANCF convergence is around one order of magnitude less than what is required by other existing methods. Limitations and advantages of the verified ANCF fluid model are discussed.

Commentary by Dr. Valentin Fuster
J. Verif. Valid. Uncert. 2018;2(4):041002-041002-22. doi:10.1115/1.4038917.

The increasing practical use of computer-aided inspection (CAI) methods requires assessment of their robustness in different contexts. This can be done by quantitatively comparing estimated CAI results with actual measurements. The objective is comparing the magnitude and dimensions of defects as estimated by CAI with those of the nominal defects. This assessment is referred to as setting up a validation metric. In this work, a new validation metric is proposed in the case of a fixtureless inspection method for nonrigid parts. It is based on using a nonparametric statistical hypothesis test, namely the Kolmogorov–Smirnov (K–S) test. This metric is applied to an automatic fixtureless CAI method for nonrigid parts developed by our team. This fixtureless CAI method is based on calculating and filtering sample points that are used in a finite element nonrigid registration (FENR). Robustness of our CAI method is validated for the assessment of maximum amplitude, area, and distance distribution of defects. Typical parts from the aerospace industry are used for this validation and various levels of synthetic measurement noise are added to the scanned point cloud of these parts to assess the effect of noise on inspection results.

Commentary by Dr. Valentin Fuster
J. Verif. Valid. Uncert. 2018;2(4):041003-041003-17. doi:10.1115/1.4039188.

A numerical estimation of discretization error for steady compressible flow solutions is performed using the error transport equation (ETE). There is a deficiency in the literature for obtaining efficient, higher order accurate error estimates for finite volume discretizations using nonsmooth unstructured meshes. We demonstrate that to guarantee sharp, higher order accurate error estimates, one must discretize the ETE to a higher order than the primal problem, a requirement not necessary for uniform meshes. Linearizing the ETE can limit the added cost, rendering the overall computational time competitive, while retaining accuracy in the error estimate. For the Navier–Stokes equations, when the primal solution is corrected using this error estimate, for the same level of solution accuracy the overall computational time is more than two times faster compared to solving the higher order primal problem. In addition, our scheme has robustness advantages, because we solve the primal problem only to lower order.

Topics: Errors
Commentary by Dr. Valentin Fuster
J. Verif. Valid. Uncert. 2018;2(4):041004-041004-9. doi:10.1115/1.4039303.

As we continue to model more complex systems, the validation of dynamical responses has come to the forefront of modeling and simulation. One form of dynamic response is when the output is a function of time. The proper evaluation of functional data over an array of desired input parameters is critical to achieving a robust validation assessment of a simulation model. We extend the correlation analysis (CORA) objective rating system to validate functional data across experimental regions. Functional regression analysis is used to generate surrogate estimations of the system response functions at points within the region where experimental observations are absent. These CORA scores provide a measure of disagreement at each desired parameter configuration. An overall score for model validity is achieved using a weighted linear combination of the individual CORA scores. Finally, an improved CORA size scoring metric is introduced.

Commentary by Dr. Valentin Fuster

Technical Brief

J. Verif. Valid. Uncert. 2018;2(4):044501-044501-5. doi:10.1115/1.4038916.

Granular and multiphase (gas–solids) kinetic theory-based models have emerged a leading modeling strategy for the simulation of particle flows. Similar to the Navier–Stokes equations of single-phase flow, although substantially more complex, kinetic theory-based continuum models are typically solved with computational fluid dynamic (CFD) codes. Under the assumptions of the so-called homogeneous cooling state (HCS), the governing equations simplify to an analytical solution describing the “cooling” of fluctuating particle velocity, or granular temperature. The HCS is used here to verify the implementation of a recent multiphase kinetic theory-based model in the open source mfix code. Results from the partial verification test show that the available implicit (backward) Euler time integration scheme converges to the analytical solution with the expected first-order rate. A second-order accurate backward differentiation formula (BDF) is also implemented and observed to converge at a rate consistent with its formal accuracy.

Commentary by Dr. Valentin Fuster

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