International Journal of Modeling, Simulation, and Scientific Computing

We review Davydychev method for calculating Feynman integrals for massive and no massive propagators, by employing Mellin–Barnes transformation and the dimensional regularization scheme, same that lead to hypergeometric functions. In particular, an example is calculated explicitly from such a method.

Quality of service (QoS) for internet traffic management requires good traffic models and good estimation of sharing network resource. A link of a network processes all traffic and it is designed with certain capacity C and buffer size B. A Generalized Markov Fluid model (GMFM), introduced by Marrón (2012), is assumed for the sources because it describes in a versatile way the traffic, allows estimation based on traffic traces, and also consistent effective bandwidth (EB) estimation can be done. QoS, interpreted as buffer overflow probability, can be estimated for GMFM through the EB estimation and solving the optimization problem presented in Courcoubetis and Siris [ Perform. Eval. 48:5–23, 2002], the so-called inf-sup formulas. In this work, we implement a code to solve the inf-sup problem and other optimization related with it, that allow us to do traffic engineering in links of data networks to calculate both, minimum capacity required when QoS and buffer size are given or minimum buffer size required when QoS and capacity are given.

We present a parallel and linear scaling implementation of the calculation of the electrostatic potential arising from an arbitrary charge distribution. Our approach is making use of the multi-resolution basis of multiwavelets. The potential is obtained as the direct solution of the Poisson equation in its Green's function integral form. In the multiwavelet basis, the formally non local integral operator decays rapidly to negligible values away from the main diagonal, yielding an effectively banded structure where the bandwidth is only dictated by the requested accuracy. This sparse operator structure has been exploited to achieve linear scaling and parallel algorithms. Parallelization has been achieved both through the shared memory (OpenMP) and the message passing interface (MPI) paradigm. Our implementation has been tested by computing the electrostatic potential of the electronic density of long-chain alkanes and diamond fragments showing (sub)linear scaling with the system size and efficent parallelization.

Establishing a mathematical supply-chain model is a proposition that has received attention due to its inherent benefits of evolving global supply-chain efficiencies. This paper discusses the prevailing relationships found within apparel supply-chain environments, and contemplates the complex issues indicated for constituting a mathematical model. Principal results identified within the data suggest, that the multifarious nature of global supply-chain activities require a degree of simplification in order to fully dilate the necessary factors which affect, each subsection of the chain. Subsequently, the research findings allowed the division of supply-chain components into subsections, which amassed a coherent method of product development activity. Concurrently, the supply-chain model was found to allow systematic mathematical formulae analysis, of cost and time, within the multiple contexts of each subsection encountered. The paper indicates the supply-chain model structure, the mathematics, and considers how product analysis of cost and time can improve the comprehension of product lifecycle management.

In fusion devices, strongly localized intensive sources of impurities may arise unexpectedly or can be created deliberately through impurity injection. The spreading of impurities from such sources is essentially three-dimensional and nonstationary phenomenon involving physical processes of extremely different time scales. Numerical modeling of such events is still a very challenging task even by using most modern computers. To diminish the calculation time drastically a "shell" model has been elaborated that allows to reduce equations for particle, parallel momentum and energy balances of various ion species to one-dimensional equations describing the time evolution of radial profiles for several most characteristic parameters. The assumptions of the "shell" approach are verified by comparing its predictions with a numerical solution of one-dimensional time-dependent transport equations.

Telematics form an important technology enabler for intelligent transportation systems. One application of the same is that by deploying on-board diagnostic devices, the signatures of vehicle vibration along with its location and time are recorded. Detailed analyses of the collected signatures offer deep insights into the state of the objects under study. Towards that objective, we carried out experiments by deploying telematics device in one of the office bus that ferries employees to office and back. Data is collected from 3-axis accelerometer, GPS speed and the time for all the journeys. In this paper, we present initial results of the above exercise by applying statistical methods to derive information through systematic analysis of the data collected over four months. It is demonstrated that the higher order derivative of the measured Z-axis acceleration samples display the properties of Weibull distribution when the time axis is replaced by the amplitude of such processed acceleration data. Such an observation offers us a method to predict future behavior where deviations from prediction are classified as context-based aberrations or progressive degradation of the system. In addition, we capture the relationship between speed of the vehicle and median of the jerk energy samples using regression analysis. That analysis is further used to identify low, normal and high JE values for a velocity and classify journey at a micro-trip (small section of a trip) level. Such results offer an opportunity to develop a robust method to model road–vehicle interaction thereby enabling us to predict such like driving behavior and condition-based maintenance, etc.

Flow through a narrow bent channel may induce topological rearrangements in a two-dimensional monodispersed dry liquid foam. We use the Cellular Potts Model to simulate a foam under a variable driving force in order to investigate the strain-rate response from these rearrangements. We observe a set of foams' behaviors ranging from elastic, viscoelastic to fluid regime. Bubble's topological rearrangements are localized and their cumulative rearrangements change linearly with time, thus nonavalanches critical behavior is found. The strain-rate affects the rate of topological rearrangements, its dependence on the drag force is nonlinear, obeying a Herschel–Bulkley-like relationship below the foam's flow point.

Several interesting phenomena have been observed simulating two-dimensional decaying turbulence in bounded domains. In this paper, an overview is given about our observations obtained by simulating freely decaying turbulence in different regular polygon shaped containers with no-slip walls. For these simulations the lattice Boltzmann method has been used as a numerical approach. The initial Reynolds number based on the container dimension was in the order of 10,000. The initial condition was the same in each simulation, therefore, we were able to compare the effect of geometrical constraints on the evolution of relevant physical quantities such as the kinetic energy and the enstrophy.

The main characteristics of millimeter-wave (MM-wave) image detector were simulated by means of accurate numerical modeling of thermophysical processes in a metamaterial MM-to-IR converter. The converter represents a multilayer structure consisting of an ultra thin resonant metamaterial absorber and a perfect emissive layer. The absorber consists of a dielectric self-supporting film that is metallized from both sides. A micro-pattern is fabricated from one side. Resonant absorption of the MM waves induces the converter heating that yields enhancement of IR emission from the emissive layer. IR emission is detected by IR camera. In this contribution an accurate numerical model for simulation of the thermal processes in the converter structure was created by using COMSOL Multiphysics software. The simulation results are in a good agreement with experimental results that validates the model. The simulation shows that the real-time operation is provided for the converter thickness less than 3 μm and time response can be improved by decreasing of the converter thickness. The energy conversion efficiency of MM waves into IR radiation is over 80%. The converter temperature increase is a linear function of a MM-wave radiation power within three orders of the dynamic range. The blooming effect and ways of its reducing are also discussed. The model allows us to choose the ways of converter structure optimization and improvement of image detector parameters.

The generalized quantum Monte Carlo algorithm is developed and used to calculate the energy, occupation numbers, and correlations functions of finite FeAs clusters in the two-orbital model at finite temperatures. The coding of quantum states made it possible to take into account complex exchange terms between the orbitals. The results for the calculation of the thermodynamic characteristics of finite two-dimensional FeAs clusters simulating iron-based superconductors have been obtained. The calculated correlation functions indicate the possibility of the effective attraction of charge carriers.

The structures of self-assembled monolayers (SAMs) of short (methyl) and long (hexyl) chain alkyl thiols on the clean gold(111) surface were modeled using for the Au–S interactions either the reactive ReaxFF potential or the well-known nonreactive Morse potential, while for the Au–Au interactions either the ReaxFF potential or an embedded-atom method (EAM). Analysis of the molecular dynamics (MD) trajectories of possible SAM structures suggests that disordering of interfacial Au atoms is definitely driven by the gold–sulphur interactions. Our MD results reveal a novel structure where two methanethiol molecules are bound to a gold adatom that has been lifted from the surface at 300 K, and the same kind of RS–Au–SR motif was also observed for hexanethiol at 600 K but not at 300 K. What is more, the above motif is only observed for the reactive ReaxFF potential. Moreover, these results are in clear agreement with recent experiments and more costly first principles-based MD simulations. These findings strongly support the use of reactive potentials such as ReaxFF for gathering an accurate description of Au–S interactions in inexpensive classical MD simulations.

Epidemics of infectious diseases have been known to recur in time. Diseases like influenza, despite intervention efforts through vaccination and targeted social distancing, continue to persist intermittently in the population. I have undertaken an analysis of a stochastic epidemic model with the hypothesis that intervention drives epidemic cycles. Intervention indeed is found to induce cycles of epidemic activity. Above a minimum intervention rate, however, activity dies out in finite time. The susceptibility structure of a community could be easily infused into the design of existing surveillance protocols. By tracking that structure, early detection of an impending outbreak is enhanced.