We consider a type of optimal switching problems with non-uniform execution delays and ramping. Such problems frequently occur in the operation of economical and engineering systems. We first provide a solution to the...
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We consider a type of optimal switching problems with non-uniform execution delays and ramping. Such problems frequently occur in the operation of economical and engineering systems. We first provide a solution to the problem by applying a probabilistic method. The main contribution is, however, a scheme for approximating the optimal control by limiting the information in the state-feedback. In a numerical example the approximation routine gives a considerable computational performance enhancement when compared to a conventional algorithm.
The mathematical model of the Baltic Sea dynamics developed at the Institute of numerical Mathematics of RAS is considered. The problem of variational assimilation of average daily data for the sea surface temperature...
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The mathematical model of the Baltic Sea dynamics developed at the Institute of numerical Mathematics of RAS is considered. The problem of variational assimilation of average daily data for the sea surface temperature (SST) is formulated and studied with the use of covariance matrices of observation data errors. Based on variational assimilation of satellite observation data, we propose an algorithm for solving the inverse problem of the heat flux reconstruction on the sea surface. The results of numerical experiments on reconstruction of the heat flux function are presented for the problem of variational assimilation of observation SST data.
In this paper, dynamical behavior of a mathematical model for the interaction of nutrient phytoplankton and its predator zooplankton is investigated numerically. Stability analysis of the phytoplankton-zooplankton mod...
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In this paper, dynamical behavior of a mathematical model for the interaction of nutrient phytoplankton and its predator zooplankton is investigated numerically. Stability analysis of the phytoplankton-zooplankton model is studied by using the fractional Routh-Hurwitz stability conditions. We have studied the local stability of the equilibrium points. Then a new numerical algorithm, as well as its modification for solving fractional differential equations (FDEs) based on the polynomial interpolation, is proposed. The algorithms are designed to estimate linear and nonlinear FDEs and they have the capability to apply for solving fractional order systems. The convergence order and stability of the fractional higher order algorithms are proved and stability regions of the algorithms are achieved. Extensive numerical simulation results are provided and compared with the literature for illustrating the effectiveness and applicability of the presented algorithms to solve fractional differential equations. The obtained analytical results are validated by numerical simulations and the global dynamics of the model system is studied. (C) 2017 Elsevier B.V. All rights reserved.
This work approximates the unknown functions based on the two-dimensional shifted Legendre polynomials operational matrix method (2D-SLPOM) for the numerical solution of two-dimensional fractional integral equations. ...
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This work approximates the unknown functions based on the two-dimensional shifted Legendre polynomials operational matrix method (2D-SLPOM) for the numerical solution of two-dimensional fractional integral equations. The present method reduces these equations to a system of algebraic equations and then this system will be solved numerically by Newton's method. Moreover, an estimation of the error bound for this algorithm will be shown by preparing some theorems. Some examples are presented to demonstrate the validity and applicability of the proposed method with respect to the two-dimensional block pulse functions method (2D-BPFs) and two-dimensional Bernstein polynomials operational matrix method (2D-BPOM). (C) 2017 Elsevier Inc. All rights reserved.
The discovery of atypical elements has become one of the most important challenges in data analysis and exploration. At the same time it is not an easy matter with difficult conditions, and not even strictly defined. ...
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The discovery of atypical elements has become one of the most important challenges in data analysis and exploration. At the same time it is not an easy matter with difficult conditions, and not even strictly defined. This article presents a ready-to-use procedure for identifying atypical elements in the sense of rarely occurring. The issue is considered in a conditional approach, where describing and conditioning variables can be multidimensional continuous with the second type also potentially categorical. The application of nonparametric concepts frees the investigated procedure from distributions of describing and conditioning variables. Ease of interpretation and completeness of the presented material lend themselves to the use of the worked out method in a wide range of tasks in various applications of data analysis in science and practice.
It is noticed that the most of the researchers having affiliation with the field of fluid science formulate the physical problems by coupling the constitutive relation of the fluid models with the Navier-Stokes equati...
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It is noticed that the most of the researchers having affiliation with the field of fluid science formulate the physical problems by coupling the constitutive relation of the fluid models with the Navier-Stokes equations. The ultimate system of partial differential equations in this direction becomes non-linear in nature due to which investigators always faced problem to narrate the flow field properties. Therefore, in this article we propose the symmetry toolkit to obtain the one parameter group of transformations for the flow controlling differential equations rather than to move-on with the so-called transformations available in literature. To propose idea we have considered the thermally magnetized Williamson fluid flow field along with heat source/sink and chemical reaction effects. The mathematical model is constructed by coupling the constitutive relation of Williamson fluid model with the Navier-Stokes equations in terms of partial differential equations. Such equations are reduced into system of ordinary differential equations by using self-constructed scaling group of transformations via symmetry analysis. The reduced system is solved by numerical algorithm. The key observations are added by means of graphs and tables. It is observed that both Weissenberg number and Hartmann number has same impact of Williamson fluid velocity. Further, Williamson fluid concentration reflects decline magnitude towards higher values of both Schmidt number and chemical reaction parameter. It is well trusted that the structuring of one parameter group of transformations for the particular flow problem will be helpful to report complete description as compared to utilizing the so-called transformations from an existing work. (C) 2019 Elsevier B.V. All rights reserved.
The inverse problem of determining a temperature-dependent thermal conductivity coefficient is studied. The study is based on the Dirichlet boundary value problem for the two-dimensional nonstationary heat equation. T...
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The inverse problem of determining a temperature-dependent thermal conductivity coefficient is studied. The study is based on the Dirichlet boundary value problem for the two-dimensional nonstationary heat equation. The cost functional is defined as the rms deviation of the surface heat flux from experimental data. For the numerical solution of the problem, an algorithm based on the modern fast automatic differentiation technique is proposed. Examples of solving the posed problem are given.
This paper presents a theoretical study on the thermal reliability of Insulated-gate bipolar transistor (IGBT) power modules. Although the Cauer thermal network (CTN) model is widely recognized as an essential tool to...
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This paper presents a theoretical study on the thermal reliability of Insulated-gate bipolar transistor (IGBT) power modules. Although the Cauer thermal network (CTN) model is widely recognized as an essential tool to analyze the thermal performance of IGBT, the heat propagation path, however, deviates from the actual situation and causing an error calculation of junction temperature. Therefore, the thermal resistance (R-th) and thermal capacity (C-th) values are optimized by the heat spreading angle of each material layer, and the influence of baseplate heat dissipation effects is fully considered by adding the heat convection mechanism to the CTN model, which includes interaction between heat conduction and heat convection, thus achieving the integrity of the heat spreading path. Effectiveness of proposed model is validated by simulation studies of finite element analysis and Simulink, the junction temperature estimation results show that the proposed model is more accurate than the conventional CTN model especially in the good dissipation conditions. Thus, accurate thermal behavior estimation could be fairly interpreted by the optimized heat spreading path.
The problem of determining the temperature-dependent thermal conductivity coefficient is studied. The study is based on the Dirichlet boundary value problem for the two-dimensional nonstationary heat equation. The cos...
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The problem of determining the temperature-dependent thermal conductivity coefficient is studied. The study is based on the Dirichlet boundary value problem for the two-dimensional nonstationary heat equation. The cost functional is defined as the rms deviation of the temperature field from experimental data. For the numerical solution of the problem, an algorithm based on the modern fast automatic differentiation technique is proposed. Examples of solving the posed problem are given.
Here, an algorithm to efficiently compute the second-Born self-energy of many-body perturbation theory is described. The core idea consists in dissecting the set of all four-index Coulomb integrals into properly chose...
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Here, an algorithm to efficiently compute the second-Born self-energy of many-body perturbation theory is described. The core idea consists in dissecting the set of all four-index Coulomb integrals into properly chosen subsets, thus avoiding to loop over those indices for which the Coulomb integrals are zero or negligible. The scaling properties of the algorithm with the number of basis functions is discussed. The computational gain is demonstrated in the case of one-particle Kohn-Sham basis for organic molecules.
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