Multidimensional upwind convection schemes for flow in porous media on structured and unstructured quadrilateral grids

Standard reservoir simulation schemes employ first order upwind schemes for approximation of the convective fluxes when multiple phases or components are present. These convective flux schemes rely upon upwind information that is determined according to grid geometry. As a consequence directional diffusion is introduced into the solution that is grid dependent. The effect can be particularly important for cases where the flow is across grid coordinate lines and is known as cross-wind diffusion.Truly higher dimensional upwind schemes that minimize cross-wind diffusion are presented for convective flow approximation on quadrilateral unstructured grids. The schemes are locally conservative and yield improved results that are essentially free of spurious oscillations. The higher dimensional schemes are coupled with full tensor Darcy flux approximations.The benefits of the resulting schemes are demonstrated for classical test problems in reservoir simulation including cases with full tensor permeability fields. The test cases involve a range of structured and unstructured grids with variations in orientation and permeability that lead to flow fields that are poorly resolved by standard simulation methods. The higher dimensional formulations are shown to effectively reduce the numerical cross-wind diffusion effect, leading to improved resolution of concentration and saturation fronts.     

The anticipative concept in warehouse optimization using simulation in an uncertain environment

The modern business environment is highly unpredictable. An anticipation approach in a real case study is presented to cope with such instability and minimize the total inventory cost without stock-outs occurring and inventory capacity being exceeded. The anticipation concept is performed using simulation models supported by inventory control algorithms on a selected sample of representative items. The inventory control algorithms include Silver–Meal, Part period balancing, Least-unit cost, and Fuzzy inventory control algorithm based on fuzzy stock-outs, highest inventory level and total cost. Transportation cost is explicitly defined as a discrete function of shipment size. The algorithms are tested on historic data. Simulation results are presented and the risk of accepting them as reliable is discussed. The process of simulation model implementation is briefly discussed to further validate the model and train order managers to use the simulation model in their order placement process.     

How to choose the simulation model for computer experiments: a local approach

In many scientific areas, non‐stochastic simulation models such as finite element simulations replace real experiments. A common approach is to fit a meta‐model, for example a Gaussian process model, a radial basis function interpolation, or a kernel interpolation, to computer experiments conducted with the simulation model. This article deals with situations where more than one simulation model is available for the same real experiment, with none being the best over all possible input combinations. From fitted models for a real experiment as well as for computer experiments using the different simulation models, a criterion is derived to identify the locally best one. Applying this criterion to a number of design points allows the design space to be split into areas where the individual simulation models are locally superior. An example from sheet metal forming is analyzed, where three different simulation models are available. In this application and many similar problems, the new approach provides valuable assistance with the choice of the simulation model to be used. Copyright © 2011 John Wiley & Sons, Ltd.     

Nonlinear vibrations of a ropeway system with moving passenger cabins

The dynamic continuous model of a carrying rope for circulating bicable aerial ropeway is formulated. To describe nonlinear in-plane vibrations excited by moving masses of passenger cabins a closed form model with Green-Lagrange deformation is developed. The equations of motion of the system are derived on the basis of Lagrange equations with Ritz approximation of cable displacements applied. Numerical example of linear and nonlinear cable vibrations is presented. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

带有缺失数据的结构方程模型中的模型选择问题

结构方程模型在社会学、教育学、医学、市场营销学和行为学中有很广泛的应用。在这些领域中,缺失数据比较常见,很多学者提出了带有缺失数据的结构方程模型,并对此模型进行过很多研究。在这一类模型的应用中,模型选择非常重要,本文将一个基于贝叶斯准则的统计量,称为L_v测度,应用到此类模型中进行模型选择。最后,本文通过一个模拟研究及实例分析来说明L_v测度的有效性及应用,并在实例分析中给出了根据贝叶斯因子进行模型选择的结果,以此来进一步说明该测度的有效性。     

FE-simulation of spatially graded gelation during adhesive's curing

In this contribution main aspects of material characterization and modelling of a curing adhesive are denoted. It is pointed out how to deal with the exothermic heat generation during curing, both, how to obtain it experimentally as well as how to account for it in the continuum mechanical an FE-modelling framework. Furthermore, a strategy to simulate spatially graded gelation processes in ANSYS® is presented. An academic simulation example completes this work. By the help of this simulation tool a better understanding of a novel manufacturing process of smart semi-finished light weight structures is ensured. (© 2015 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Mathematical modeling of resonant linear vibratory conveyor with electromagnetic excitation: simulations and experimental results

Vibratory conveyors are commonly used in industry for transporting a wide variety of bulk and particulate materials. Various control structures based on state observers can be found in the literature. However, they are mostly based on simplified mathematical models. In order to obtain a more precise state observer, and consequently better performance and (or) control quality, more detailed mathematical model of the resonant vibratory conveyor is required. Mathematical model of a resonant linear vibratory conveyor driven by an electromagnetic excitation force is presented. Derivation of the mathematical model is based on the kinetic and potential energies, dissipative function of the mechanical system, and Lagrangian formulation. A simulation model is implemented on the basis of the derived mathematical equations. The simulation results are presented and compared to the experimental results obtained by a real industrial vibratory conveyor.     

Modeling and dynamics of a two-line kite

A mathematical model of a kite connected to the ground by two straight tethers of varying lengths is presented and used to study the traction force generated by kites flying in cross-wind conditions. The equations of motion are obtained by using a Lagrangian formulation, which yields a low-order system of ordinary differential equations free of constraint forces. Two parameters are chosen for the analysis. The first parameter is the wind velocity. The second parameter is one of the stability derivatives of the aerodynamic model: the roll response to the sideslip angle, known also as effective dihedral. This parameter affects significantly the lateral dynamics of the kite. It has been found that when the effective dihedral is below a certain threshold, the kite follows stable periodic trajectories, and naturally flies in cross-wind conditions while generating a high tension along both tethers. This result indicates that kite-based propulsion systems could operate without controlling tether lengths if kite design, including the dihedral and sweep angles, is done appropriately. If both tether lengths are varied out-of-phase and periodically, then kite dynamics can be very complex. The trajectories are chaotic and intermittent for values of the effective dihedral below a certain negative threshold. It is found that tether tensions can be very similar with and without tether length modulation if the parameters of the model are well-chosen. The use of the model for pure traction applications of kites is discussed.     

An Efficient Thermo-Kinematic (ETK) Model for Long-Time Simulation of High Speed Railway Brake Dynamics

High speed railway brakes transfer a large amount of kinetic energy into heat during the brake operation. Due to its design one major problem is tapered wear, which could significantly reduce brake performance and safety as well as increase aftermarket costs. Modeling and simulation of these brake systems is rather complicated with respect to the coupled multiphysics, multiscaled phenomena, friction and wear, especially on long time scale. Here, we present the so-called Efficient Thermo-Kinematic (ETK) model, which include the complexities of the multiphysics of the brake process in the efficient way. Using this model, we are able to proceed the simulation of the brake dynamics in long-time scale. The partial differential equations are derived based on the coupled manner. The simulation with ETK model shows reasonable results with very fast computational time. The ratio of computing time to real time can reach 1:2000 (with a standard personal computer). Thus, investigations on tapered wear can be performed not only in one brake operation but in many times of brake operations. The simulation results will support the development process of railway brakes in order to mitigate tapered wear of the brake pads. (© 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

A robust fuzzy k-means clustering model for interval valued data

Summary  In this paper a robust fuzzy k-means clustering model for interval valued data is introduced. The peculiarity of the proposed model is the capability to manage anomalous interval valued data by reducing the effects of such outliers in the clustering model. In the interval case, the concept of anomalous data involves both the center and the width (the radius) of an interval. In order to show how our model works the results of a simulation experiment and an application to real interval valued data are discussed.     

Numerical solution of a PDE model for a ratchet-cap pricing with BGM interest rate dynamics

In this paper we present a new numerical method to price an interest rate derivative. The financial product consists of a particular ratchet cap contract which contains a set of ratchet caplets. For this purpose, we first pose the PDE pricing model for each ratchet caplet by means of Feynman-Kac theorem. The underlying interest rates are the forward LIBOR rates, the dynamics of which are assumed to follow the recently introduced BGM (LMM) market model. For the set of PDEs associated to the ratchet caplets pricing problems, we propose a second order Crank-Nicolson characteristics time discretization scheme combined with a finite element discretization in the interest rate variables. In order to illustrate the performance of the numerical methods, we present an academic test and a real example of a particular ratchet cap pricing. In the second case, a comparison between the results obtained by Monte Carlo simulation and the proposed method is presented.     

带有不可忽略缺失数据的半参数再生散度模型的贝叶斯分析

半参数再生散度模型是再生散度模型和半参数回归模型的推广,包括了半参数广义线性模型和广义部分线性模型等特殊类型.讨论的是该模型在响应变量和协变量均存在非随机缺失数据情形下参数的Bayes估计和基于Bayes因子的模型选择问题.在分析中,采用了惩罚样条来估计模型中的非参数成分,并建立了Bayes层次模型;为了解决Gibbs抽样过程中因参数高度相关带来的混合性差以及因维数增加导致出现不稳定性的问题,引入了潜变量做为添加数据并应用了压缩Gibbs抽样方法,改进了收敛性;同时,为了避免计算多重积分,利用了M-H算法估计边缘密度函数后计算Bayes因子,为模型的选择比较提供了一种准则.最后,通过模拟和实例验证了所给方法的有效性.     

MIP approaches for the integrated berth allocation and quay crane assignment and scheduling problem

In this paper we consider an integrated berth allocation and quay crane assignment and scheduling problem motivated by a real case where a heterogeneous set of cranes is considered. A first mathematical model based on the relative position formulation (RPF) for the berth allocation aspects is presented. Then, a new model is introduced to avoid the big-M constraints included in the RPF. This model results from a discretization of the time and space variables. For the new discretized model several enhancements, such as valid inequalities, are introduced. In order to derive good feasible solutions, a rolling horizon heuristic (RHH) is presented. A branch and cut approach that uses the enhanced discretized model and incorporates the upper bounds provided by the RHH solution is proposed. Computational tests are reported to show (i) the quality of the linear relaxation of the enhanced models; (ii) the effectiveness of the exact approach to solve to optimality a set of real instances; and (iii) the scalability of the RHH based on the enhanced mathematical model which is able to provide good feasible solutions for large size instances.     

Stochastic Model of Conditional Non-stationary Time Series of the Wind Chill Index in West Siberia

In this paper, we propose a stochastic model of the conditional time series of the wind chill index. The model is based on the inverse distribution function method and on the normalization method for simulation of the non-Gaussian non-stationary random processes as well as on the method of conditional distributions for simulation of the conditional Gaussian processes. In the framework of the approach considered, two types of conditions (point conditions and interval conditions) are imposed on the time series. The model in question was verified using the real data collected at the weather stations located in West Siberia (Russia). It is shown that the simulated trajectories are close in their statistical properties to the real time series. The model proposed was used for stochastic forecasting of the wind chill index and the results of the numerical experiments have shown that the accuracy of the short-term forecasts is high enough.

     

Incorporating human behaviour in simulation models of screening for breast cancer

Simulation modelling is widely used in many industries in order to assess and evaluate alternative options and to test strategies or operating rules which are too complex to be modelled analytically. Simulation software has developed its capability in parallel with the growth in computing power since the 1980s. However in practice, the results from the most sophisticated and complex simulation model may not truly reflect what happens in the real world, because such models do not account for human behaviour. For example, in the domain of healthcare simulation is often used to evaluate the outcomes from medical interventions such as new drug treatments. However in reality patients may not complete the course of a prescribed medication, perhaps because they find the side-effects unpleasant. A simulation study designed to evaluate this medication which ignores such behavioural factors may give unreliable results. In this paper we describe a model for screening for breast cancer which includes behavioural factors to model women’s decisions to attend for mammography. The model results indicate that increasing attendance through education or publicity campaigns can be equally as effective as decreasing the intervals between screens. This would have considerable cost implications for healthcare providers.     

Zur Berechnung der Geschossabweichung unter dem Einfluss eines Seitenwindes

Summary The first order correction which should be made to thez-coordinate of the standard trajectory of a projectile to account for a cross-wind is given by (1). It is shown that this formula is a very good approximation also for angles of departure near 90°.     

Modelling and Simulation of Milling Forces Using an Arbitrary Lagrangian–Eulerian Finite Element Method and Support Vector Regression

A new method is presented to predict milling forces synthetically. Firstly, the 3D simulation model of the milling process is established using the arbitrary Lagrangian–Eulerian finite element method. And the simulated accuracy is calibrated by milling tests. Then the simulation model is taken as a virtual milling test system to replace extensive real milling experiments. Secondly, the specific cutting coefficients in the mechanistic milling forces model are identified by the support vector regression method using the training sample generated from the established virtual milling test system. Lastly, this methodology was validated by the slot milling operation of 2024-T3 aluminum sheets. The results show that this new approach can dramatically eliminate the experimental machining work and achieve good estimation accuracy.     

Simulation of quasi-dimensional combustion model for predicting diesel engine performance

In order to improve the precision of quasi-dimensional combustion model for predicting diesel engine performance and promote the real time operating performance of the simulation model, a new phase-divided spray mixing model is proposed and the quasi-dimensional combustion model of diesel engine working process is developed. The software MATLAB/Simulink is utilized to build the quasi-dimensional combustion model of diesel engine working process, and the performance for diesel engine is simulated. The simulation results agree with experimental data quite well. The comparisons between them show that the relative error of power and brake specific fuel consumption is less than 2.8% and the relative error of nitric oxide and soot emissions is less than 9.1%. By utilization of this simulation model with personal computer, the average computational time for one diesel engine working process is 36 s, which presents good real time operating performance of the model. At the same time, the influence of parameters in calculation of air entrainment on prediction precision of diesel engine’s simulation model is analyzed.     

On estimation of measurement error models with replication under heavy-tailed distributions

Measurement error (errors-in-variables) models are frequently used in various scientific fields, such as engineering, medicine, chemistry, etc. In this work, we consider a new replicated structural measurement error model in which the replicated observations jointly follow scale mixtures of normal (SMN) distributions. Maximum likelihood estimates are computed via an EM type algorithm method. A closed expression is presented for the asymptotic covariance matrix of those estimators. The SMN measurement error model provides an appealing robust alternative to the usual model based on normal distributions. The results of simulation studies and a real data set analysis confirm the robustness of SMN measurement error model.     

Fuzzy facility location-allocation problem under the Hurwicz criterion

Facility location-allocation (FLA) problem has been widely studied by operational researchers due to its many practical applications. Many researchers have studied the FLA problem in a deterministic environment. However, the models they proposed cannot accommodate satisfactorily various customer demands in the real world. Thus, we consider the FLA problem with uncertainties. In this paper, a new model named α-cost model under the Hurwicz criterion is presented with fuzzy demands. In order to solve this model, the simplex algorithm, fuzzy simulations and a genetic algorithm are integrated to produce a hybrid intelligent algorithm. Finally, some numerical examples are presented to illustrate the effectiveness of the proposed algorithm.