Conference on Advances in Uncertainty Quantification Methods, Algorithms and Applications (UQAW 2015)http://hdl.handle.net/10754/6240472024-05-23T15:30:04Z2024-05-23T15:30:04Z721A Game Theoretical Approach for Cooperative Environmentally Friendly Cellular Networks Powered by the Smart GridGhazzai, HakimYaacoub, EliasAlouini, Mohamed-Slimhttp://hdl.handle.net/10754/6240722024-03-13T12:03:07Z2015-01-07T00:00:00Zdc.title: A Game Theoretical Approach for Cooperative Environmentally Friendly Cellular Networks Powered by the Smart Grid
dc.contributor.author: Ghazzai, Hakim; Yaacoub, Elias; Alouini, Mohamed-Slim
2015-01-07T00:00:00ZA Hybrid DGTD-MNA Scheme for Analyzing Complex Electromagnetic SystemsLi, PengJiang, Li-JunBagci, Hakanhttp://hdl.handle.net/10754/6240922023-10-30T22:42:49Z2015-01-07T00:00:00Zdc.title: A Hybrid DGTD-MNA Scheme for Analyzing Complex Electromagnetic Systems
dc.contributor.author: Li, Peng; Jiang, Li-Jun; Bagci, Hakan
dc.description.abstract: A hybrid electromagnetics (EM)-circuit simulator for analyzing complex systems consisting of EM devices loaded with nonlinear multi-port lumped circuits is described. The proposed scheme splits the computational domain into two subsystems: EM and circuit subsystems, where field interactions are modeled using Maxwell and Kirchhoff equations, respectively. Maxwell equations are discretized using a discontinuous Galerkin time domain (DGTD) scheme while Kirchhoff equations are discretized using a modified nodal analysis (MNA)-based scheme. The coupling between the EM and circuit subsystems is realized at the lumped ports, where related EM fields and circuit voltages and currents are allowed to “interact’’ via numerical flux. To account for nonlinear lumped circuit elements, the standard Newton-Raphson method is applied at every time step. Additionally, a local time-stepping scheme is developed to improve the efficiency of the hybrid solver. Numerical examples consisting of EM systems loaded with single and multiport linear/nonlinear circuit networks are presented
to demonstrate the accuracy, efficiency, and applicability of the proposed solver.
2015-01-07T00:00:00ZA multilevel adaptive reaction-splitting method for SRNsMoraes, AlvaroTempone, RaulVilanova, Pedrohttp://hdl.handle.net/10754/6240862023-10-30T22:42:18Z2015-01-07T00:00:00Zdc.title: A multilevel adaptive reaction-splitting method for SRNs
dc.contributor.author: Moraes, Alvaro; Tempone, Raul; Vilanova, Pedro
dc.description.abstract: In this work, we present a novel multilevel Monte Carlo method for kinetic simulation of stochastic reaction networks specifically designed for systems in which the set of reaction channels can be adaptively partitioned into two subsets characterized by either “high” or “low” activity. To estimate expected values of observables of the system, our method bounds the global computational error to be below a prescribed tolerance, within a given confidence level. This is achieved with a computational complexity of order O (TOL-2).We also present a novel control variate technique which may dramatically reduce the variance of the coarsest level at a negligible computational cost. Our numerical examples show substantial gains with respect to the standard Stochastic Simulation Algorithm (SSA) by Gillespie and also our previous hybrid Chernoff tau-leap method.
2015-01-07T00:00:00ZA Novel Time Domain Method for Characterizing Plasmonic Field InteractionsUysal, Ismail EnesUlku, Huseyin ArdaBagci, Hakanhttp://hdl.handle.net/10754/6240772024-03-13T12:02:43Z2015-01-07T00:00:00Zdc.title: A Novel Time Domain Method for Characterizing Plasmonic Field Interactions
dc.contributor.author: Uysal, Ismail Enes; Ulku, Huseyin Arda; Bagci, Hakan
2015-01-07T00:00:00ZA Polynomial Chaos Expansion technique for correlated variablesNavarro, MaríaWitteveen, JeroenBlom, Jokehttp://hdl.handle.net/10754/6240562023-10-30T22:42:40Z2015-01-07T00:00:00Zdc.title: A Polynomial Chaos Expansion technique for correlated variables
dc.contributor.author: Navarro, María; Witteveen, Jeroen; Blom, Joke
2015-01-07T00:00:00ZA Time Marching Scheme for Solving Volume Integral Equations on Nonlinear ScatterersBagci, Hakanhttp://hdl.handle.net/10754/6241022023-11-30T01:26:16Z2015-01-07T00:00:00Zdc.title: A Time Marching Scheme for Solving Volume Integral Equations on Nonlinear Scatterers
dc.contributor.author: Bagci, Hakan
dc.description.abstract: Transient electromagnetic field interactions on inhomogeneous penetrable scatterers can be analyzed by solving time domain volume integral equations (TDVIEs). TDVIEs are oftentimes solved using marchingon-in-time (MOT) schemes. Unlike finite difference and finite element schemes, MOT-TDVIE solvers require discretization of only the scatterers, do not call for artificial absorbing boundary conditions, and are more robust to numerical phase dispersion. On the other hand, their computational cost is high, they suffer from late-time instabilities, and their implicit nature makes incorporation of nonlinear constitutive relations more difficult. Development of plane-wave time-domain (PWTD) and FFT-based schemes has significantly reduced the computational cost of the MOT-TDVIE solvers. Additionally, latetime instability problem has been alleviated for all practical purposes with the development of accurate integration schemes and specially designed temporal basis functions. Addressing the third challenge is the topic of this presentation. I will talk about an explicit MOT scheme developed for solving the TDVIE on scatterers with nonlinear material properties. The proposed scheme separately discretizes the TDVIE and the nonlinear constitutive relation between electric field intensity and flux density. The unknown field intensity and flux density are expanded using half and full Schaubert-Wilton-Glisson (SWG) basis functions in space and polynomial temporal interpolators in time. The resulting coupled system of the discretized TDVIE and constitutive relation is integrated in time using an explicit P E(CE) m scheme to yield the unknown expansion coefficients. Explicitness of time marching allows for straightforward incorporation of the nonlinearity as a function evaluation on the right hand side of the coupled system of equations. Consequently, the resulting MOT scheme does not call for a Newton-like nonlinear solver. Numerical examples, which demonstrate the applicability of the proposed MOT scheme to analyzing electromagnetic interactions on Kerr-nonlinear scatterers will be presented.
2015-01-07T00:00:00ZAdaptive Surrogate Modeling for Response Surface Approximations with Application to Bayesian InferencePrudhomme, Sergehttp://hdl.handle.net/10754/6241112023-11-30T01:26:38Z2015-01-07T00:00:00Zdc.title: Adaptive Surrogate Modeling for Response Surface Approximations with Application to Bayesian Inference
dc.contributor.author: Prudhomme, Serge
dc.description.abstract: The need for surrogate models and adaptive methods can be best appreciated if one is interested in parameter estimation using a Bayesian calibration procedure for validation purposes. We extend here our latest work on error decomposition and adaptive refinement for response surfaces to the development of surrogate models that can be substituted for the full models to estimate the parameters of Reynolds-averaged Navier-Stokes models. The error estimates and adaptive schemes are driven here by a quantity of interest and are thus based on the approximation of an adjoint problem. We will focus in particular to the accurate estimation of evidences to facilitate model selection. The methodology will be illustrated on the Spalart-Allmaras RANS model for turbulence simulation.
2015-01-07T00:00:00ZAn A Posteriori Error Estimate for Symplectic Euler Approximation of Optimal Control ProblemsKarlsson, Peer JesperLarsson, StigSandberg, MattiasSzepessy, AndersTempone, Raulhttp://hdl.handle.net/10754/6240972023-10-30T22:42:32Z2015-01-07T00:00:00Zdc.title: An A Posteriori Error Estimate for Symplectic Euler Approximation of Optimal Control Problems
dc.contributor.author: Karlsson, Peer Jesper; Larsson, Stig; Sandberg, Mattias; Szepessy, Anders; Tempone, Raul
dc.description.abstract: This work focuses on numerical solutions of optimal control problems. A time discretization error representation is derived for the approximation of the associated value function. It concerns Symplectic Euler solutions of the Hamiltonian system connected with the optimal control problem. The error representation has a leading order term consisting of an error density that is computable from Symplectic Euler solutions. Under an assumption of the pathwise convergence of the approximate dual function as the maximum time step goes to zero, we prove that the remainder is of higher order than the leading error density part in the error representation. With the error representation, it is possible to perform adaptive time stepping. We apply an adaptive algorithm originally developed for ordinary differential equations.
2015-01-07T00:00:00ZAn Efficient Explicit Time Marching Scheme for Solving the Time Domain Magnetic Field Volume Integral EquationSayed, Sadeed BUlku, Huseyin ArdaBagci, Hakanhttp://hdl.handle.net/10754/6240782024-03-13T12:02:55Z2015-01-07T00:00:00Zdc.title: An Efficient Explicit Time Marching Scheme for Solving the Time Domain Magnetic Field Volume Integral Equation
dc.contributor.author: Sayed, Sadeed B; Ulku, Huseyin Arda; Bagci, Hakan
2015-01-07T00:00:00ZAn Efficient Simulation Method for Rare EventsRached, Nadhir B.Benkhelifa, FatmaKammoun, AblaAlouini, Mohamed-SlimTempone, Raulhttp://hdl.handle.net/10754/6240842023-10-30T22:42:25Z2015-01-07T00:00:00Zdc.title: An Efficient Simulation Method for Rare Events
dc.contributor.author: Rached, Nadhir B.; Benkhelifa, Fatma; Kammoun, Abla; Alouini, Mohamed-Slim; Tempone, Raul
dc.description.abstract: Estimating the probability that a sum of random variables (RVs) exceeds a given threshold is a well-known challenging problem. Closed-form expressions for the sum distribution do not generally exist, which has led to an increasing interest in simulation approaches. A crude Monte Carlo (MC) simulation is the standard technique for the estimation of this type of probability. However, this approach is computationally expensive, especially when dealing with rare events. Variance reduction techniques are alternative approaches that can improve the computational efficiency of naive MC simulations. We propose an Importance Sampling (IS) simulation technique based on the well-known hazard rate twisting approach, that presents the advantage of being asymptotically optimal for any arbitrary RVs. The wide scope of applicability of the proposed method is mainly due to our particular way of selecting the twisting parameter. It is worth observing that this interesting feature is rarely satisfied by variance reduction algorithms whose performances were only proven under some restrictive assumptions. It comes along with a good efficiency, illustrated by some selected simulation results comparing the performance of our method with that of an algorithm based on a conditional MC technique.
2015-01-07T00:00:00Z