On the construction of discrete filters for symmetry-preserving regularization models

Since direct numerical simulations cannot be computed at high Reynolds numbers, a dynamically less complex formulation is sought. In the quest for such a formulation, we consider regularizations of the convective term that preserve the symmetry and conservation properties exactly. This requirement yielded a novel class of regularizations [Verstappen R. On restraining the production of small scales of motion in a turbulent channel flow. Comput Fluids 2008;37:887–97.] that restrains the convective production of smaller and smaller scales of motion in an unconditionally stable manner, meaning that the velocity cannot blow up in the energy-norm (in 2D also: enstrophy-norm). The numerical algorithm used to solve the governing equations must preserve the symmetry and conservation properties too. To do so, one of the most critical issues is the discrete filtering. The method requires a list of properties that, in general, is not preserved by classical filters for LES unless they are imposed a posteriori. In the present paper, we propose a novel class of discrete filters that preserves such properties per se. They are based on polynomial functions of the discrete diffusive operator, , with the general form . Then, the coefficients, d_m, follow from the requirement that, at the smallest grid scale k_c, the amount by which the interactions between the wavevector-triples (k_c, k_c − q, q) are damped must become virtually independent of the qth Fourier-mode. This allows an optimal control of the subtle balance between convection and diffusion at the smallest grid scale to stop the vortex-stretching. Finally, the resulting filters are successfully tested for the Burgers’ equation.     

Buoyancy convection in a cavity with mutually orthogonal heated plates

Buoyancy driven convection in a square cavity induced by two mutually orthogonal arbitrarily placed heated thin plates is studied numerically under isothermal and isoflux boundary conditions. The flow is assumed to be two-dimensional. The coupled governing equations were solved by the finite difference method using the Alternating Direction Implicit technique and Successive Over Relaxation method. The steady state results are depicted in terms of streamline and isotherm plots. It is found that the resulting convection pattern is stronger for the isothermal boundary condition. A better overall heat transfer can be achieved by placing one of the plates far away from the center of the cavity for isothermal boundary condition and near the center of the cavity for isoflux boundary condition.     

Implementation of regularization for separable nonlinear least squares problems

This paper considers a class of separable nonlinear least squares problems in which a model can be represented as a linear combination of nonlinear functions. A regularized nonlinear parameter optimization approach is presented for coping with the potential ill-conditioned problem of parameter divergence. Together with a regularization parameter detection technique, Tikhonov regularization and truncated singular value decomposition are utilized in the estimation of the linear parameters if the nonlinear parameters are changed during the parameter optimization process, which centers on a nonlinear parameter search using the Levenberg-Marquardt algorithm. Benefiting from the regularization in parameter optimization, the potential ill-conditioned issue can be avoided, and the multi-step-ahead forecasting accuracy of the estimated model may be largely improved. The usefulness of this approach is illustrated by means of a chaotic time-series prediction and nonlinear industrial process modeling.     

Effect of temperature gradient orientation on the characteristics of mixed convection flow in a lid-driven square cavity

The effect of temperature gradient orientation on the fluid flow and heat transfer in a lid-driven differentially heated square cavity is investigated numerically. The transport equations are solved using the high-order compact scheme. Four cases are considered depending on the direction of temperature gradient imposed. The differentially heated top and bottom walls result in gravitationally stable and unstable temperature gradients. While the differentially heated left and right side walls lead to assisting and opposing buoyancy effects. The governing parameters are Pr = 0.7 and Ri = 0.1, 1, and 10. It is found that both Richardson number and direction of temperature gradient affect the flow patterns, heat transport processes, and heat transfer rates in the cavity. Computed average Nusselt number indicates that the heat transfer rate increases with decreasing Ri regardless the orientation of temperature gradient imposed. And the assisting buoyancy flows have best performance on heat transport over the other three cases.     

TLM modeling of a probe‐coupled cylindrical cavity based on compact wire model in the cylindrical mesh

This article describes an implementation of a compact wire model into the three‐dimensional transmission‐line matrix (TLM) cylindrical mesh for the purpose of an efficient analysis of probe‐coupled cylindrical microwave cavity devices. Because of a cylindrical grid structure and empirical nature of the compact model, this implementation has to take into account a change of wire model parameters with a variable cross section of the TLM nodes through which a wire conductor passes. The model accuracy has been experimentally verified and compared with the corresponding results reached by the TLM method based on a rectangular grid in order to consider its advantages. © 2011 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2012.     

Numerical simulation of turbulent flow in the inlet region of a smooth pipe

An algebraic-Q4 turbulent eddy viscosity model expresses the eddy viscosity as a solution of a quartic (Q4) equation. The model is applied to numerical simulation of developing turbulent flow in the inlet region of a smooth pipe. Predictions of the flow characteristics, such as velocity profiles accross and along a pipe, pressure drop along a pipe are found in good agreement with experimental data.     

一类三关节体操机器人的类等效建模

无力矩驱动模式的电机驱动器使得三关节体操机器人控制难度增加,但具有实际意义.针对该类机器人系统,提出了基于＂类等效＂思想的简化动力学模型,该模型由刚体动力学和加速度驱动两个子模型构成.利用拉格朗日法建立刚体动力学方程;使用频率响应法得到加速度驱动模型的伯德图并确定了其阶次,根据阶跃响应曲线确定其纯滞后;使用改进的遗传算法辨识模型参数.通过对简化前后的模型进行对比实验以及简化模型的稳定控制实验,验证了简化模型的有效性和优越性.     

一类非线性系统的在线建模新方法

为减少非线性系统的Volterra级数模型在线建模的计算量，根据多模型合成的思想。提出一种基于预设模型在线合成被测系统当前Volterra级数模型的新方法。建立了模型合成的公式和方法．仿真实验表明。该方法具有较高的建模精度。能有效减少Volterra模型在线建模的计算量。并且易于工程实现．     

Experimental and numerical modeling of the effect of solid surface on NOx emission in the combustion chamber of a water heater

A combined experimental and CFD modeling study of the turbulent non-premixed natural gas on a laboratory scale has been performed. Effect of solid surface enhancement in combustion chamber on the flame temperature and NO emission was investigated. The solid surface called as filling material (FM) was cylindrical and was placed coaxially in the center of combustion chamber. The temperature and NO distribution in the combustion chamber were compared for different geometries of the filling material. The diameters of the filling materials were 25 and 30 cm with two lengths of 20 and 40 cm. Experimental study has been carried out on a fire tube water heater. The flame temperature on the center line of the combustion chamber, gas temperature and NO emission in the combustion chamber were measured. The actual geometry of the fire tube water heater and the burner were modeled and then analyzed by the FLUENT code. Turbulent diffusion flames were investigated numerically using a finite volume method for the solution of the conservation and reaction equations governing the problem. The measured values were specified as the boundary conditions. The elemental analysis of the natural gas was taken as a mixture of hydrocarbon and air was the oxidizer. The standard k-ε model was used for the modeling of the turbulence phenomena in the combustor. The non-premixed combustion model was chosen. In the conserved scalar approach, turbulence effects were accounted for with the help of an assumed shape probability density function or PDF. The discrete ordinates (DO) radiation model was used for modeling of the radiative heat transfer in the combustion room. The model results were compared with the experimental results. The model results were in good agreement with the measurements. The filling material provided the recirculation of the cooler gases into the flame. The recirculation reduced the oxygen concentration in the flame and controlled the flame temperature. It was found that the filling material with the diameter bigger than the flame diameter increased the heat transfer rate in the back flow around the flame.     

Development of a knowledge library for automated watershed modeling

In this work, we develop a library of components for building semi-distributed watershed models. The library incorporates basic modeling knowledge that allows us to adequately model different water fluxes and nutrient loadings on a watershed scale. It is written in a formalism compliant with the equation discovery tool ProBMoT, which can automatically construct watershed models from the components in the library, given a conceptual model specification and measured data. We apply the proposed modeling methodology to the Ribeira da Foupana catchment to extract a set of viable hydrological models. By specifying the conceptual model and using the knowledge library, two different hydrological models are generated. Both models are automatically calibrated against measurements and the model with the lower root mean squared error (RMSE) value is selected as an appropriate hydrological model for the selected study area.     

First principle modeling and predictive control of a continuous biodiesel plant

Typically, the large-scale production of biodiesel involves continuous operation plants. Also, the final biodiesel product has to comply with specifications imposed by standards of quality in order to be marketable. These quality constraints must be satisfied during the production at the minimum possible operating cost, in order to make the process economically viable. In this context, a nonlinear model predictive controller (NMPC) is applied to control the oil transesterification section of a continuous biodiesel plant. The controller determines the optimal profiles of the process variables using a nonlinear mechanistic model of the whole transesterification section. The model describes the dynamics of the composition and temperature of the liquid mixture in the reactors and in the decanters, as well as of the decanters interface level. The capability of the proposed NMPC strategy to improve the process economic performance and to enforce the final biodiesel specifications is demonstrated by simulation.     

Proportional data modeling via selection and estimation of a finite mixture of scaled Dirichlet distributions

This paper proposes an unsupervised algorithm for learning a finite mixture of scaled Dirichlet distributions. Parameters estimation is based on the maximum likelihood approach, and the minimum message length (MML) criterion is proposed for selecting the optimal number of components. This research work is motivated by the flexibility issues of the Dirichlet distribution, the widely used model for multivariate proportional data, which has prompted a number of scholars to search for generalizations of the Dirichlet. By introducing the extra parameters of the scaled Dirichlet, several useful statistical models could be obtained. Experimental results are presented using both synthetic and real datasets. Moreover, challenging real-world applications are empirically investigated to evaluate the efficiency of our proposed statistical framework.     

Development of a semantic product modeling system for initial hull structure in shipbuilding

In the initial stage of ship design, designers represent geometry, arrangement, and dimension of hull structures, which correspond to product model information, with 2D geometric primitives such as points, lines, arcs, and drawing symbols on 2D drawings. However, designers must translate the product model information defined on the 2D drawings more intelligently in the following design stages. Thus, design semantics could be lost and design processes that follow could be delayed because of errors by mistranslating the information. Here, design semantics mean design intents of the designer, that is, functions and structures which the product must have.In this study, a semantic product model data structure of an initial ship hull structure was proposed, and a semantic product modeling system was developed based on the proposed data structure. The proposed data structure can store semantic product model information such as product design results with the use of 2D wire frame geometrical data, part attributes, and design knowledge. Hence, this information can be used to generate a 3D solid model and production material information for CAPP as needed.The applicability of the proposed data structure and the developed system was verified by applying them to the deadweight 300,000 ton of Very Large Crude oil Carrier’s product modeling procedure. The application results showed that the proposed data structure and the developed system can be efficiently used for overall initial ship design environment.     

Combining fuzzy cognitive maps with agent-based modeling: Frameworks and pitfalls of a powerful hybrid modeling approach to understand human-environment interactions

Agent-based modeling (ABM) is an established technique to capture human-environment interactions in socio-ecological systems. As a micro-model, it explicitly represents each agent, such that heterogeneous decision-making processes (e.g. based on the beliefs and experiences of stakeholders) can anticipate the socio-environmental consequences of aggregated individual behaviors. In contrast to ABM, Fuzzy Cognitive Mapping takes a macro-level view of the world that represents causal connections between concepts rather than individual entities. Researchers have expressed interest in reconciling the two, i.e. taking a hybrid approach and drawing of the strengths of each to more accurately model socio-ecological interactions. The intuition is to take FCMs, which can be quickly developed using participatory modeling tools and use them to create a virtual population of agents with sophisticated decision-making processes. In this paper, we detail two ways in which this combination can be done, and highlight the key questions that modelers need to be mindful of.