Accurate Multi-Phase Flow Simulation in Faulted Reservoirs Using Mimetic Finite Difference Methods on Polyhedral Cells

Faulted reservoirs are commonly modeled by corner-point grids. Since the two-point flux approximation (TPFA) method is not consistent on non-orthogonal grids, multi-phase flow simulation using TPFA on corner-point grids may have significant discretization errors if grids are not K-orthogonal. To improve the simulation accuracy, we developed a novel method where the faults are modeled by polyhedral cells, and mimetic finite difference (MFD) methods are used to solve flow equations. We use a cut-cell approach to build the mesh for faulted reservoirs. A regular orthogonal grid is first constructed,and then fault planes are added by dividing cells at fault planes. Most cells remain orthogonal while irregular non-orthogonal polyhedral cells can be formed with multiple cell divisions. We investigated three spatial discretization methods for solving the pressure equation on general polyhedral grids, including the TPFA, MFD and TPFA-MFD hybrid methods. In the TPFA-MFD hybrid method, the MFD method is only applied to part of the domain while the TPFA method is applied to rest of the domain. We compared flux accuracy between TPFA and MFD methods by solving a single-phase flow problem. The reference solution is obtained on a rectangular grid while the same problem is solved by TPFA and MFD methods on a grid with distorted cells near a fault. Fluxes computed using TPFA exhibit larger errors in the vicinity of the fault while fluxes computed using MFD are still as accurate as the reference solution. We also compared saturation accuracy of two-phase (oil and water) flow in faulted reservoirs when the pressure equation is solved by different discretization methods. Compared with the reference saturation solution, saturation exhibits non-physical errors near the fault when pressure equation is solved by the TPFA method. Since the MFD method yields accurate fluxes over general polyhedral grids, the resulting saturation solutions match the reference saturation solutions with an enhanced accuracy when the pressure equation is solved by the MFD method. Based on the results of our simulation studies, the accuracy of the TPFA-MFD hybrid method is very close to the accuracy of the MFD method while the TPFA-MFD hybrid method is computationally cheaper than the MFD method.

Novel method for identifying residual prestress force in simply supported concrete girder-bridges

Testing methods are required for estimating prestress losses in Prestressed Concrete (PC) girder-bridges. They mainly include destructive approaches which cause significant damages. Conversely, dynamic nondestructive methods are unsuitable. Given these findings, a novel method for identifying residual prestress force in simply supported PC girder-bridges was implemented. Following the vertical load application in a three-point bending, the method estimates the prestress force by measuring the vertical deflection at a quarter or, alternatively, at the midspan of the PC girder-bridge. The method also requires information regarding its flexural rigidity. Particularly, the initial tangent Young’s modulus must be evaluated by compression tests on cores drilled at its quarter and midspan cross-sections after three-point bending. In absence of the geometric and/or material properties, the flexural rigidity can be estimated according to free vibrations. Secondly, the method comprises a reference solution, or a finite element model of the PC girder-bridge, in which the prestress force is unknown. Thirdly, the measured deflection becomes a parameter of the prestress force identification process. Accurate identifications are obtained when the deflection, under a higher vertical load, was precisely measured and the flexural rigidity was determined using reference solution and initial tangent Young’s modulus. In this article, the novel method was simulated on a simply supported PC beam-bridge subjected to time-dependent prestress losses for ≈9.5 months in the laboratory.

Some features of the problems of computational optimization in the computer-integrated systems

For quality control in computer-integrated systems, it is assumed that the calculation of control signals is based on mathematical models of control objects. When solving the equations of the dynamics of the control object, it is necessary to take into account the limited computing resources of computer-integrated systems, which requires the choice of an effective method of solving equations, provided that the required accuracy of calculations. The paper considers a method for solving computational optimization problems in computer-integrated systems based on the proposed optimality criteria. A method is proposed based on the estimation of the discrepancy between the obtained and the reference solution to estimate the global error. The solution is accepted, the accuracy of which is two orders of magnitude higher than the required modeling accuracy.

SPX Benchmark Part I: Results of Static Neutronics

In the paper, the specification of a new neutronics benchmark for a large Sodium cooled Fast Reactor core and results of modelling by different participants are presented. The neutronics benchmark describes the core of the French sodium cooled reactor Superphénix at its startup configuration, which in particular was used for experimental measurement of reactivity characteristics. The benchmark consists of the detailed heterogeneous core specification for neutronic analysis and results of the reference solution. Different core geometries and thermal conditions from cold “as fabricated” up to full power were considered. The reference Monte Carlo solution of Serpent 2 includes data on multiplication factor, power distribution, axial and radial reaction rates distribution, reactivity coefficients and safety characteristics, control rods worth, kinetic data. The results of modelling with seven other solutions using deterministic and Monte Carlo methods are also presented and compared to the reference solution. The comparisons results demonstrate appropriate agreement of evaluated characteristics. The neutronics results will be used in the second phase of the benchmark for evaluation of transient behaviour of the core.

In vitro dissolution characteristics of patent, generic and similar brands of naproxen in various dissolution media

Purpose: To investigate the dissolution properties of various brands of naproxen in four dissolution media in order to forecast their biological availability. Methods: Dissolution tests were carried out in a dissolution tester with 48 tablets of different naproxen brands in 900 mL of 0.1 M phosphate buffer, pH 7.4. Subsequently, the medium was modified with 600 mL of buffer plus 300 mL of cola drink, grapefruit or milk. Each sample was taken and brought to a concentration approximating that of a reference solution. Absorbance at 332 nm was determined and the dissolution, Q, was calculated (Q values ≥ 80.0 ± 5 % were acceptable). Results: Dissolution in buffer was > 85 %. In cola drink, it was < 80 %, while in grapefruit juice, it was in the range of 7 - 68 %. Using 2-way ANOVA, these media and the three naproxen brands showed significant differences (F = 68.90, p = 0.0000; F = 23.18, p = 0.0000). With Fisher's LSD test, two of these media contributed consistently to dissolution, and the three drug brands showed statistically different dissolution profiles (p ≤ 0.05). Conclusion: Caution must be exercised cola drink, grapefruit juice and milk are used to administered naproxen as the biological availability of the drug may be altered.

IMPLEMENTASI PEMILIHAN MOTOR BEKAS MENGGUNAKAN METODE AHP-TOPSIS

A motorbike is a type of transportation that runs on an engine and has two wheels. Used is something that has been called not new. Human need for transportation means the most in the use of motorbikes. Economic limitations of some people choose to buy used motorbikes. In the selection, it is difficult to help consumers determine the choice of vehicle to be purchased. This is because there are so many types of motorbikes in one brand. This study aims to recommend a reference solution as a basis for consideration in selecting a used motorbike. This decision support system in solving this problem uses AHP and TOPSIS. The AHP method was chosen because it produces weighted criteria. Meanwhile, TOPSIS was chosen because for ranking determination, it is expected to provide the best used motorbike recommendation solutions to buyers

Discretization Error Estimation in Subsonic, Transonic and Supersonic Flows of an Inviscid Fluid Over a Bump

This paper presents a solution verification exercise for the simulation of subsonic, transonic and supersonic flows of an inviscid fluid over a circular arc (bump). Numerical simulations are performed with a pressure-based, single-phase compressible flow solver. Sets of geometrically similar grids covering a wide range of refinement ratios have been generated. The goal of these grids is twofold: obtain a reference solution from power series expansion fits applied to the finest grids; check the numerical uncertainties obtained from coarse grids that do not guarantee monotonic convergence of the quantities of interest. The results show that even with very fine grids it is not straightforward to define a reference solution from power series expansions. The level of discretization errors required to obtain reliable reference solutions implies iterative errors reduced to machine accuracy, which may be extremely time consuming even in two-dimensional inviscid flows. Quantitative assessment of the estimated uncertainties for coarse grids depends on the selected reference solution.

Fidelity Assessment of Real-Time Hybrid Substructure Testing: a Review and the Application of Artificial Neural Networks

Real-Time Hybrid Substructure (RTHS) testing is a commonly used method to investigate the dynamical influence of a component on a mechanical system. In RTHS, a part of the dynamical system is tested experimentally, while the remaining structure is simulated numerically in a co-simulation. There are several error sources in the RTHS loop that distort the test outcome. To investigate the reliability of the test, the fidelity of the test must be quantified. In many engineering applications, however, there is no reference solution available to which the test outcome can be validated against. This work reviews currently existing accuracy measures used in RTHS. Furthermore, using Artificial Neural Networks (ANN) to predict the fidelity of the RTHS test outcome when no reference solution is available is proposed. Appropriate input features for the network, such as dynamic properties of the system and existing error indicators, are discussed. ANN training was performed on a data set from a virtual RTHS (vRTHS) simulation of a dynamical system with contact. The training process was successful, meaning that the correlation between the ANN prediction and the true fidelity value was > 99 %. Then, the network was applied to data of experimental RTHS tests of the same dynamical system and achieved a correlation of 98 %, which proves that the relation found by the ANN captured the relation between the chosen input features and the error measure. The application of the trained ANN to data from a linear vRTHS test revealed that further improvement of the network and the choice of input features is necessary. This work suggests that ANNs could be a meaningful tool to predict the fidelity of the RTHS test outcome in the absence of a reference solution, especially if more data from different RTHS tests were aggregated to train them.