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At least 1,801 records · Page 100

Numerical multi-scaling method to solve the linear stochastic partial differential equations

In this paper, we propose a multi-scaling method to solve a class of the stochastic partial differential equations (SPDEs) of Itô-type. By this method, we approximate the solution of the SPDEs with strongly elliptic operator on a finite domain. The method is based on B-spline wavelet approximations; some of these functions are reshaped to satisfy on boundary conditions exactly. We prove the consistency and stability of the method. Illustrative examples are included to demonstrate the validity and applicability of our proposed technique.

97 MATHEMATICS AND COMPUTING↗

Disjunctive linear separation conditions and mixed-integer formulations for aircraft conflict resolution

In this paper, we address the aircraft conflict resolution problem in air traffic control. We introduce new mixed-integer programming formulations for aircraft conflict resolution with speed, heading and altitude control which are based on disjunctive linear separation conditions. We first examine the two-dimensional aircraft conflict resolution problem with speed and heading control represented as continuous decision variables. We show that the proposed disjunctive linear separation conditions are equivalent to the classical nonlinear conditions for aircraft separation. Further, we characterise conflict-free trajectories based on aircraft velocity bounds and propose a simple pre-processing algorithm to identify aircraft pairs which are either always conflict-free, or which cannot be separated using speed and heading control only. We then incorporate altitude control and propose a lexicographic optimisation formulation that aims to minimise the number of flight level changes before resolving outstanding conflicts via two-dimensional velocity control. The proposed mixed-integer programming formulations are nonconvex, and we propose convex relaxations, decomposition methods and constraint generation algorithms to solve the two-dimensional and lexicographic optimisation formulations to guaranteed optimality. Numerical experiments on four types of conflict resolution benchmarking instances are conducted to test the performance of the proposed mixed-integer formulations. Further, the proposed method is compared against two benchmarks based on state-of-the-art approaches for the aircraft conflict resolution problem. Our numerical results show that the proposed method largely outperforms both benchmarks in terms of runtime and is able to solve significantly more instances to global optimality.

97 MATHEMATICS AND COMPUTING↗

Regularizing the linearly extrapolated BDF2 scheme for incompressible flows with time relaxation

This paper presents a highly-efficient finite element scheme for the time relaxation model (TRM). The efficiency is achieved through the second-order BDF2 time-stepping scheme with linear extrapolation (BDF2LE). The accuracy of the scheme is also greatly enhanced through the use of the divergence-free Scott-Vogeulis finite elements, and van Cittert approximate deconvolution. A complete finite element analysis is provided, which includes rigorous proofs for the stability, well-possessedness, and convergence of both velocity and pressure solutions. Furthermore, we also demonstrate that the inclusion of the linear time relaxation term preserves the long-time stability of the unregularized BDF2LE scheme. Finally, numerical experiments are presented that demonstrate the added stability and accuracy that time relaxation can provide.

97 MATHEMATICS AND COMPUTING↗

Stochastic solution of population balance equations for reactor networks

This work presents a sequential modular approach to solve a generic network of reactors with a population balance model using a stochastic numerical method. Full-coupling to the gas-phase is achieved through operator-splitting. The convergence of the stochastic particle algorithm in test networks is evaluated as a function of network size, recycle fraction and numerical parameters. These test cases are used to identify methods through which systematic and statistical error may be reduced, including by use of stochastic weighted algorithms. The optimal algorithm was subsequently used to solve a one-dimensional example of silicon nanoparticle synthesis using a multivariate particle model. This example demonstrated the power of stochastic methods in resolving particle structure by investigating the transient and spatial evolution of primary polydispersity, degree of sintering and TEM-style images. Highlights: •An algorithm is presented to solve reactor networks with a population balance model. •A stochastic method is used to solve the population balance equations. •The convergence and efficiency of the reported algorithms are evaluated. •The algorithm is applied to simulate silicon nanoparticle synthesis in a 1D reactor. •Particle structure is reported as a function of reactor length and time.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A point implicit time integration technique for slow transient flow problems

We introduce a point implicit time integration technique for slow transient flow problems. The method treats the solution variables of interest (that can be located at cell centers, cell edges, or cell nodes) implicitly and the rest of the information related to same or other variables are handled explicitly. The method does not require implicit iteration; instead it time advances the solutions in a similar spirit to explicit methods, except it involves a few additional function(s) evaluation steps. Moreover, the method is unconditionally stable, as a fully implicit method would be. This new approach exhibits the simplicity of implementation of explicit methods and the stability of implicit methods. It is specifically designed for slow transient flow problems of long duration wherein one would like to perform time integrations with very large time steps. Because the method can be time inaccurate for fast transient problems, particularly with larger time steps, an appropriate solution strategy for a problem that evolves from a fast to a slow transient would be to integrate the fast transient with an explicit or semi-implicit technique and then switch to this point implicit method as soon as the time variation slows sufficiently. We have solved several test problems that result from scalar or systems of flow equations. Our findings indicate the new method can integrate slow transient problems very efficiently; and its implementation is very robust.

42 ENGINEERING↗

Approximate analytic solutions to coupled nonlinear Dirac equations

Here, we consider the coupled nonlinear Dirac equations (NLDEs) in 1+11+1 dimensions with scalar–scalar self-interactions g 1 2 /2($\bar{ψ}$ψ) 2 + g 2 2 /2($\bar{Φ}$Φ) 2 + g 2 3 ($\bar{ψ}$ψ)($\bar{Φ}$Φ) as well as vector–vector interactions g 1 2 /2($\bar{ψ}$γμψ)($\bar{ψ}$γμψ) + g 2 2 /2($\bar{Φ}$γμΦ)($\bar{Φ}$γμΦ) + g 2 3 ($\bar{ψ}$γμψ)($\bar{Φ}$γμΦ). Writing the two components of the assumed rest frame solution of the coupled NLDE equations in the form ψ=e –iω1t R 1 cosθ,R 1 sinθΦ=e –iω2t R 2 cosη,R 2 sinη, and assuming that θ(x),η(x) have the same functional form they had when g3 = 0, which is an approximation consistent with the conservation laws, we then find approximate analytic solutions for Ri(x) which are valid for small values of g 3 2 /g 2 2 and g 3 2 /g 1 2 . In the nonrelativistic limit we show that both of these coupled models go over to the same coupled nonlinear Schrödinger equation for which we obtain two exact pulse solutions vanishing at x → ±∞.

97 MATHEMATICS AND COMPUTING↗

Coarse-Grained Density Functional Theory Predictions via Deep Kernel Learning

Scalable electronic predictions are critical for soft materials design. Recently, the Electronic Coarse-Graining (ECG) method was introduced to renormalize all-atom quantum chemical (QC) predictions to coarse-grained (CG) resolutions using deep neural networks (DNNs). While DNNs can learn complex representations that prove challenging for kernel-based methods, they are susceptible to overfitting and the overconfidence of uncertainty estimations. Here, we develop ECG within a GPU-accelerated Deep Kernel Learning (DKL) framework to enable CG QC predictions using range-separated hybrid density functional theory (DFT), obtaining a 107 speedup relative to naive all-atom QC. By treating the predicted electronic properties as random Gaussian Processes, DKL incorporates CG mapping degeneracy by learning the distribution of electronic energies as a function of CG configuration. DKL-ECG accurately reproduces molecular orbital energies from range-separated DFT while facilitating efficient training via active learning using the uncertainties provided by DKL. Further, we show that while active learning algorithms enable efficient sampling of a more diverse configurational space relative to random sampling, all explored query methods exhibit comparable performance for the examined system. We attribute this result to the significant overlap of the feature space and output property distributions across multiple temperatures.

97 MATHEMATICS AND COMPUTING↗

Continuum Microkinetic Rate Theory of Lattice Systems: Formalization, Current Limitations, and a Possible Basis for Continuum Rate Theory

A broad class of reaction networks are controlled not by any thermodynamic ensemble but by rates and are referred to as “kinetically constrained”. Here in this paper, microkinetic rate theory is extended into a model of arbitrarily complex reaction networks. This microkinetic rate theory takes a form where the constraints imposed by kinetically constrained systems apply naturally. This model is compared to numerically complete results and is shown to be quantitatively predictive. Model deviations are shown to emerge for systems with incomplete mixing. Finally, this model is analytical and may serve as a basis for device and continuum scale rate modeling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The impedance problem of wave diffraction by a strip with higher order boundary conditions

This work is devoted to analyse an impedance boundary-transmission problem for the Helmholtz equation originated by a problem of wave diffraction by an infinite strip with higher order imperfect boundary conditions. A constructive approach of operator relations is built, which allows a transparent interpretation of the problem in an operator theory framework. In particular, different types of operator relations are exhibited for different types of operators acting between Lebesgue and Sobolev spaces on a finite interval and the positive half-line. All this has consequences in the understanding of the structure of this type of problems. In particular, a Fredholm characterization of the problem is obtained in terms of the initial space order parameters. At the request of the author and the Proceedings Editor the above article has been replaced with a corrected version. The original PDF file supplied to AIP Publishing contained an error in the title of the article. The original title appeared as: 'The Impedance Problem of Wave Diffraction by a trip with Higher Order Boundary Conditions.' This article has been replaced and the title now appears correctly online. The corrected article was published on 8 November 2013.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Minimal blow-up solutions of mass-critical inhomogeneous Hartree equation

In this paper, we are concerned with the Cauchy problem of the inhomogeneous Hartree equation: iu{sub t}=−Δu−k(x)(∫{sub R{sup N}}(k(y))/(|x−y|{sup 2}) |u(t,y)|{sup 2}dy)u(t,x), x∈R{sup N}, N ⩾ 3. First, we establish the mass concentration property of the blow-up solutions. Second, we show that the blow-up solutions with minimal mass should concentrate at a critical point of k. Finally, under certain assumptions on global maximum points of k we establish nonexistence of such solutions.

97 MATHEMATICS AND COMPUTING↗

Problem of two-level hierarchical minimax program control the final state of regional social and economic system in the presence of risks

This article discusses a discrete-time dynamical system consisting of a set a controllable objects (region and forming it municipalities). The dynamics each of these is described by the corresponding vector nonlinear discrete-time recurrent vector equations and its control system consist from two levels: basic (control level I) that is dominating and subordinate level (control level II). Both levels have different criterions of functioning and united a priori by determined informational and control connections defined in advance. In this paper we study the problem of optimization of guaranteed result for program control by the final state of regional social and economic system in the presence of risks. For this problem we proposed in this work an economical and mathematical model of two-level hierarchical minimax program control the final state of regional social and economic system in the presence of risks and the general scheme for its solving.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Stabilization of the stochastically forced equilibria for nonlinear discrete-time systems with incomplete information

A stabilization problem of the equilibrium of stochastically forced nonlinear discrete-time system with incomplete information is considered. Our approach uses a regulator which synthesizes the required stochastic sensitivity of the equilibrium. Mathematically, this problem is reduced to the solution of some quadratic matrix equations. A description of attainability sets and algorithms for regulators design is given. The general results are applied to the suppression of unwanted large-amplitude oscillations around the equilibria of the stochastically forced Verhulst model with noisy observations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Some functional limit theorems for compound Cox processes

An improved version of the functional limit theorem is proved establishing weak convergence of random walks generated by compound doubly stochastic Poisson processes (compound Cox processes) to Lévy processes in the Skorokhod space under more realistic moment conditions. As corollaries, theorems are proved on convergence of random walks with jumps having finite variances to Lévy processes with variance-mean mixed normal distributions, in particular, to stable Lévy processes.

97 MATHEMATICS AND COMPUTING↗

Mathematical modelling of the beam under axial compression force applied at any point – the buckling problem

The study is devoted to stability of simply supported beam under axial compression. The beam is subjected to an axial load located at any point along the axis of the beam. The buckling problem has been desribed and solved mathematically. Critical loads have been calculated. In the particular case, the Euler’s buckling load is obtained. Explicit solutions are given. The values of critical loads are collected in tables and shown in figure. The relation between the point of the load application and the critical load is presented.

97 MATHEMATICS AND COMPUTING↗

On mixing of Markov measures associated with b−bistochastic QSOs

New majorization is in advantage as compared to the classical one since it can be defined as a partial order on sequences. We call it as b−order. Further, the defined order is used to establish a bistochasticity of nonlinear operators in which, in this study is restricted to the simplest case of nonlinear operators i.e quadratic operators. The discussions in this paper are based on bistochasticity of Quadratic Stochastic Operators (QSO) with respect to the b−order. In short, such operators are called b−bistochastic QSO. The main objectives in this paper are to show the construction of non-homogeneous Markov measures associated with QSO and to show the defined measures associated with the classes of b−bistochastic QSOs meet the mixing property.

97 MATHEMATICS AND COMPUTING↗

On a class of summability methods for multiple Fourier series

The paper shows that the same properties which hold for the classical (C,1)-means are preserved for a sufficiently large class of summability methods for multiple Fourier series involving rectangular partial sums. More precisely, Fourier series of continuous functions are uniformly summable by these methods, and Fourier series of functions from the class L(ln{sup +} L){sup m-1} (T{sup m}) are summable almost everywhere. Bibliography: 6 titles.

97 MATHEMATICS AND COMPUTING↗

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