constructing general orthogonal fractional factorial split plot designs while the orthogonal design of split plot fractional factorial experiments has received much attention already there are still major voids in the literature first designs with one or more factors acting at more than two levels have not yet been considered second published work on nonregular fractional factorial split plot designs was either based only on plackett burman designs or on small nonregular designs with limited numbers of factors in this article we present a novel approach to designing general orthogonal fractional factorial split plot designs one key feature of our approach is that it can be used to construct two level designs as well as designs involving one or more factors with more than two levels moreover the approach can be used to create two level designs that match or outperform alternative designs in the literature and to create two level designs that cannot be constructed using existing methodology our new approach involves the use of integer linear programming and mixed integer linear programming and for large design problems it combines integer linear programming with variable neighborhood search we demonstrate the usefulness of our approach by constructing two level split plot designs of 16 96 runs an 81 run three level split plot design and a 48 run mixed level split plot design supplementary materials for this article are available online 2015 american statistical association and the american society for quality

the hybridized discontinuous galerkin method for implicit large eddy simulation of transitional turbulent flows abstract we present a high order implicit large eddy simulation iles approach for transitional aerodynamic flows the approach encompasses a hybridized discontinuous galerkin dg method for the discretization of the navier stokes ns equations and a parallel preconditioned newton gmres solver for the resulting nonlinear system of equations the combination of hybridized dg methods with an efficient solution procedure leads to a high order accurate ns solver that is competitive to alternative approaches such as finite volume and finite difference codes in terms of computational cost the proposed approach is applied to transitional flows over the naca 65 18 10 compressor cascade and the eppler 387 wing at reynolds numbers up to 460 000 grid convergence studies are presented and the required resolution to capture transition at different reynolds numbers is investigated numerical results show rapid convergence and excellent agreement with experimental data in short this work aims to demonstrate the potential of high order iles for simulating transitional aerodynamic flows this is illustrated through numerical results and supported by theoretical considerations

assessment of variational multiscale models for the large eddy simulation of turbulent incompressible flows in this work we study the performance of some variational multiscale models vms in the large eddy simulation les of turbulent flows we consider vms models obtained by different subgrid scale approximations which include either static or dynamic subscales linear or nonlinear multiscale splitting and different choices of the subscale space after a brief review of these models we discuss some implementation aspects particularly relevant to the simulation of turbulent flows namely the use of a skew symmetric form of the convective term and the computation of projections when orthogonal subscales are used we analyze the energy conservation and numerical dissipation of the alternative vms formulations which is numerically evaluated in the numerical study we have considered three well known problems the decay of homogeneous isotropic turbulence the taylor green vortex problem and the turbulent flow in a channel we compare the results obtained using different vms models paying special attention to the effect of using orthogonal subscale spaces the vms results are also compared against classical les scheme based on filtering and the dynamic smagorinsky closure altogether our results show the tremendous potential of vms for the numerical simulation of turbulence further we study the sensitivity of vms to the algorithmic constants and analyze the behavior in the small time step limit we have also carried out a computational cost comparison of the different formulations out of these experiments we can state that the numerical results obtained with the different vms formulations as far as they converge are quite similar however some choices are prone to instabilities and the results obtained in terms of computational cost are certainly different the dynamic orthogonal subscales model turns out to be best in terms of efficiency and robustness

algorithmic construction of efficient fractional factorial designs with large run sizes fractional factorial ff designs are widely used in practice and typically are chosen according to the minimum aberration criterion a sequential algorithm is developed for constructing efficient ff designs a construction procedure is proposed that allows a design to be constructed only from its minimum aberration projection in the sequential buildup process to efficiently identify nonisomorphic designs designs are categorized according to moment projection pattern a fast isomorphism checking procedure is developed by matching the factors using their delete one factor projections this algorithm is used to completely enumerate all 128 run designs of resolution 4 all 256 run designs of resolution 4 up to 17 factors all 512 run designs of resolution 5 all 1024 run designs of resolution 6 and all 2048 and 4 096 run designs of resolution 7 a method is proposed for constructing minimum aberration ma designs using only a partial catalog of some good designs three approaches to constructing good de

simulations of a turbulent flow past a sudden expansion a sensitivity analysis large eddy simulation is used to study the flow behind a pair of symmetric backward facing steps as reported in the literature the flow exhibits an asymmetric pattern characterized by the deflection of the jet toward one of the walls the large eddy simulation results are compared with laser doppler anemometry measurements showing the ability of the present numerical tool to capture the complex features of the flow furthermore a sensitivity study is conducted to assess the influence of the grid resolution the inflow boundary the channel width and the step size on the flowfield the flow was found to be only weakly sensitive to the grid assuring the quality of the simulation results the inflow boundary influences the mean results only marginally unless low frequency fluctuations are applied in this case the flowfield recovers a mean symmetry with suppression of the jet bending the jet mean bending has also been shown to increase with the step size h and to decrease with increasing channel width

a likelihood approximation for locally stationary processes a new approximation to the gaussian likelihood of a multivariate locally stationary process is introduced it is based on an approximation of the inverse of the covariance matrix of such processes the new quasi likelihood is a generalisation of the classical whittle likelihood for stationary processes for parametric models asymptotic normality and efficiency of the resulting estimator are proved since the likelihood has a special local structure it can be used for nonparametric inference as well this is briefly sketched for different estimates

chebyshev legendre super spectral viscosity method for nonlinear conservation laws in this paper a super spectral viscosity method using the chebyshev differential operator of high order d s sqrt 1 x 2 opx s is developed for nonlinear conservation laws the boundary conditions are treated by a penalty method compared with the second order spectral viscosity method the super one is much weaker while still guaranteeing the convergence of the bounded solution of the chebyshev galerkin chebyshev collocation or legendre galerkin approximations to nonlinear conservation laws which is proved by compensated compactness arguments

minimum aberration fractional factorial designs with large n xu has cataloged 165 minimum aberration ma regular fractional factorial ff designs with 2 levels and large run sizes n 128 m 8 64 factors n 256 m 9 28 109 119 n 512 m 10 25 238 246 n 1024 m 11 24 488 501 n 2048 m 12 23 and n 4096 m 13 24 such an extensive catalog was produced because of an improved algorithm we extend the catalog by 36 ma 2 level regular ff designs n 256 m 29 36 100 108 n 512 m 26 29 n 1024 m 25 28 n 2048 m 24 32 and n 4096 m 25 26 although such enumeration problems are notoriously difficult with increased n and or m we brought the newly solved problems within computational reach by changing the vital isomorphism check component of xu s algorithm here we present a new compact graph for solving regular design isomorphism problems and use the nauty program to solve the corresponding graph isomorphism problems supplemental appendices are available online

nonparametric quasi maximum likelihood estimation for gaussian locally stationary processes this paper deals with nonparametric maximum likelihood estimation for gaussian locally stationary processes our nonparametric mle is constructed by minimizing a frequency domain likelihood over a class of functions the asymptotic behavior of the resulting estimator is studied the results depend on the richness of the class of functions both sieve estimation and global estimation are considered our results apply in particular to estimation under shape constraints as an example autoregressive model fitting with a monotonic variance function is discussed in detail including algorithmic considerations a key technical tool is the time varying empirical spectral process indexed by functions for this process a bernstein type exponential inequality and a central limit theorem are derived these results for empirical spectral processes are of independent interest

variable neighborhood search principles and applications abstract systematic change of neighborhood within a possibly randomized local search algorithm yields a simple and effective metaheuristic for combinatorial and global optimization called variable neighborhood search vns we present a basic scheme for this purpose which can easily be implemented using any local search algorithm as a subroutine its effectiveness is illustrated by solving several classical combinatorial or global optimization problems moreover several extensions are proposed for solving large problem instances using vns within the successive approximation method yields a two level vns called variable neighborhood decomposition search vnds modifying the basic scheme to explore easily valleys far from the incumbent solution yields an efficient skewed vns svns heuristic finally we show how to stabilize column generation algorithms with help of vns and discuss various ways to use vns in graph theory i e to suggest disprove or give hints on how to prove conjectures an area where metaheuristics do not appear to have been applied before

slex analysis of multivariate nonstationary time series we develop a procedure for analyzing multivariate nonstationary time series using the slex library smooth localized complex exponentials which is a collection of bases each basis consisting of waveforms that are orthogonal and time localized versions of the fourier complex exponentials under the slex framework we build a family of multivariate models that can explicitly characterize the time varying spectral and coherence properties every model has a spectral representation in terms of a unique slex basis before selecting a model we first decompose the multivariate time series into nonstationary components with uncorrelated nonredundant spectral information the best slex model is selected using the penalized log energy criterion which we derive in this article to be the kullback leibler distance between a model and the slex principal components of the multivariate time series the model selection criterion takes into account all of the pairwise cross correlation simultaneously in the multivar

blocked nonregular two level factorial designs this article discusses the optimal blocking criteria for nonregular two level designs we extend the optimal blocking criteria of cheng and wu to nonregular designs by adapting the g and g2 minimum aberration criteria discussed by tang and deng to define word length pattern for nonregular designs we extend the notion of word to nonregular designs through a polynomial representation of factorial designs we define treatment resolution and block resolution for evaluating the degrees of aliasing and confounding we propose four new criteria which we use to search for optimal blocking schemes of 12 run 16 run and 20 run two level orthogonal arrays

wavelet processes and adaptive estimation of the evolutionary wavelet spectrum this article defines and studies a new class of non stationary random processes constructed from discrete non decimated wavelets which generalizes the cramer fourier representation of stationary time series we define an evolutionary wavelet spectrum ews which quantifies how process power varies locally over time and scale we show how the ews may be rigorously estimated by a smoothed wavelet periodogram and how both these quantities may be inverted to provide an estimable time localized autocovariance we illustrate our theory with a pedagogical example based on discrete non decimated haar wavelets and also a real medical time series example

construction of orthogonal two level designs of user specified resolution where n 2 k fractional two level factorial designs are often used in the early stages of an investigation to screen for important factors traditionally 2 n k fractional factorial designs of resolution iii iv or v have been used for this purpose when the investigator is able to specify the set of nonnegligible factorial effects it is sometimes possible to obtain an orthogonal design with fewer runs than a standard textbook design by searching within a wider class of designs called parallel flats designs the run sizes in this class of designs do not necessarily need to be powers of 2 we discuss an algorithm for constructing orthogonal parallel flats designs to meet user specifications several examples illustrate the use of the algorithm

inference for non stationary time series regression with or without inequality constraints summary we consider statistical inference for time series linear regression where the response and predictor processes may experience general forms of abrupt and smooth non stationary behaviours over time meanwhile the regression parameters may be subject to linear inequality constraints a simple and unified procedure for structural stability checks and parameter inference is proposed in the case where the regression parameters are constrained the methodology proposed is shown to be consistent whether or not the true regression parameters are on the boundary of the restricted parameter space via utilizing an asymptotically invariant geometric property of polyhedral cones

using the folded over 12 run plackett burman design to consider interactions this article demonstrates that the folded over 12 run plackett burman design is useful for considering up to 12 factors in 24 runs even if one anticipates that some two factor interactions may be significant the properties of this design are investigated and a sequential procedure for analyzing the data from such a design is proposed the performance of the procedure is investigated through the analysis of real and constructed examples and through a small simulation study applications to other folded over plackett burman designs are also briefly discussed

a spectral vanishing viscosity method for large eddy simulations a new simulation approach for high reynolds number turbulent flows is developed combining concepts of monotonicity in nonlinear conservation laws with concepts of large eddy simulation the spectral vanishing viscosity svv first introduced by e tadmor siam j numer anal 26 30 1989 is incorporated into the navier stokes equations for controlling high wavenumber oscillations unlike hyperviscosity kernels the svv approach involves a second order operator which can be readily implemented in standard finite element codes in the work presented here discretization is performed using hierarchical spectral hp methods accommodating effectively an ab initio intrinsic scale separation the key result is that monotonicity is enforced via svv leading to stable discretizations without sacrificing the formal accuracy i e exponential convergence in the proposed discretization several examples are presented to demonstrate the effectiveness of the new approach including a comparison with eddy viscosity spectral les of turbulent channel flow in its current implementation the svv approach for controlling the small scales is decoupled from the large scales but a procedure is proposed that will provide coupling similar to the classical les formulation

on the gibbs phenomenon and its resolution the nonuniform convergence of the fourier series for discontinuous functions and in particular the oscillatory behavior of the finite sum was already analyzed by wilbraham in 1848 this was later named the gibbs phenomenon this article is a review of the gibbs phenomenon from a different perspective the gibbs phenomenon as we view it deals with the issue of recovering point values of a function from its expansion coefficients alternatively it can be viewed as the possibility of the recovery of local information from global information the main theme here is not the structure of the gibbs oscillations but the understanding and resolution of the phenomenon in a general setting the purpose of this article is to review the gibbs phenomenon and to show that the knowledge of the expansion coefficients is sufficient for obtaining the point values of a piecewise smooth function with the same order of accuracy as in the smooth case this is done by using the finite expansion series to construct a different rapidly convergent approximation

large eddy simulation of shock turbulence interaction the approximate deconvolution model adm for large eddy simulation les is adapted for use with a central fourth order finite volume jameson type scheme widely applied for aerodynamics calculations of industrial interest with adm an approximation of the unfiltered solution is obtained by repeated filtering and given a good approximation of the unfiltered solution the nonlinear terms of the filtered navier stokes equation are computed directly the effect of scales not represented on the numerical grid is modeled by a relaxation regularization involving a secondary filter operation and a relaxation parameter the supersonic turbulent boundary layer along a compression ramp at a freestream mach number of m 3 and a reynolds number based on free stream quantities and the mean momentum thickness at inflow of re 1685 is computed to evaluate the ability of adm to represent discontinuities and turbulent flow regions it was observed that a unified modeling of discontinuities and turbulence required a local adaptation of the secondary filter used for the relaxation regularization the les results are compared with corresponding filtered direct numerical simulation dns data very good agreement between the filtered dns and the les is observed for the mean fluctuating and averaged wall quantities

numerical dissipation vs subgrid scale modelling for large eddy simulation this study presents an alternative way to perform large eddy simulation based on a targeted numerical dissipation introduced by the discretization of the viscous term it is shown that this regularisation technique is equivalent to the use of spectral vanishing viscosity the flexibility of the method ensures high order accuracy while controlling the level and spectral features of this purely numerical viscosity a pao like spectral closure based on physical arguments is used to scale this numerical viscosity a priori it is shown that this way of approaching large eddy simulation is more efficient and accurate than the use of the very popular smagorinsky model in standard as well as in dynamic version the main strength of being able to correctly calibrate numerical dissipation is the possibility to regularise the solution at the mesh scale thanks to this property it is shown that the solution can be seen as numerically converged conversely the two versions of the smagorinsky model are found unable to ensure regularisation while showing a strong sensitivity to numerical errors the originality of the present approach is that it can be viewed as implicit large eddy simulation in the sense that the numerical error is the source of artificial dissipation but also as explicit subgrid scale modelling because of the equivalence with spectral viscosity prescribed on a physical basis

numerical diffusion in the fct algorithm revisited numerical diffusion in a flux corrected transport fct algorithm embedded in a navier stokes solver tiny3d has been analytically and numerically studied for flows where density variations can be neglected it is found that numerical diffusion can be analytically expressed in a form similar to that of viscous diffusion the effective total viscosity can be written as an effective viscosity which is the sum of the physical and numerical viscosities a low mach number laminar boundary layer flow is used to test the analytical model of numerical diffusion a series of simulations in which the amount of numerical diffusion is varied show results consistent with predictions of boundary layer theory when the effective total viscosity is used the minimum required numerical viscosity to meet the linear stability condition and the lower and upper limits of the cell reynolds number are also derived

aeroacoustics of t junction merging flow this paper reports a numerical study of the aeroacoustics of merging flow at t junction the primary focus is to elucidate the acoustic generation by the flow unsteadiness the study is conducted by performing direct aeroacoustic simulation approach which solves the unsteady compressible navier stokes equations and the perfect gas equation of state simultaneously using the conservation element and solution element method for practical flows the reynolds number based on duct width is usually quite high 105 in order to properly account for the effects of flow turbulence a large eddy simulation methodology together with a wall modeling derived from the classical logarithm wall law is adopted the numerical simulations are performed in two dimensions and the acoustic generation physics at different ratios of side branch to main duct flow velocities vr 0 5 0 67 1 0 2 0 are studied both the levels of unsteady interactions of merging flow structures and the efficiency of acoustic generation are obser

short note straightforward high order numerical dissipation via the viscous term for direct and large eddy simulation in this short note we show how to use a highly accurate finite difference scheme to compute second derivatives in the navier stokes equations while ensuring targeted numerical dissipation this approach essentially non conservative is shown to be close to an upwind method and is straightforward to implement with a negligible computational extra cost the benefit offered by the resulting discrete operator is illustrated for the direct computation of sound in aeroacoustics and in the more general context of large eddy simulation through connections with hyperviscosity and spectral vanishing viscosity

the basic equations for the large eddy simulation of turbulent flows in complex geometry abstract the equations for large eddy simulation les of turbulent flows are derived by applying a filtering operation to the navier stokes equations les of inhomogeneous turbulent flows requires the use of filters with variable filter width the use of such filters invalidates the standard derivation of the basic equations for the filtered fields since the filtering operation in general does not commute with the operation of differentiation in this paper an alternate definition of the filtering operation based on the mapping function of the nonuniform grid is introduced it is shown that with this modified definition the filtering and differentiation operations commute up to an error which is second order in the filter width it is also shown that the commutation error can be expressed in terms of the filtered field and its derivatives as an asymptotic series in the square of the filter width these results are then applied to the navier stokes equations to derive the basic equations satisfied by the filtered fields

effective viscosity in the simulation of spatially evolving shear flows with monotonic fct models abstract the global numerical diffusion of a model for the low mach number simulation of free mixing layers is investigated the numerical model solves the inviscid time dependent conservation equations for mass momentum and energy for ideal gases the equations are solved using an explicit flux corrected transport fct algorithm directional timestep splitting techniques on structured grids and appropriate inflow and outflow boundary conditions effective measurement of the numerical diffusion of the model in uniform grids is performed by comparison of the laminar spread of the simulated mixing layers with that predicted by boundary layer theory the results show that the residual numerical diffusion of the fct model can emulate physical viscosity for laminar shear flows at moderately high reynolds numbers the global numerical diffusion is not very sensitive to changes in free stream velocity ratio and can be reduced in a predictable way by refining the grid spacing

risk bounds for model selection via penalization performance bounds for criteria for model selection are devel oped using recent theory for sieves the model selection criteria are based on an empirical loss or contrast function with an added penalty term moti vated by empirical process theory and roughly proportional to the number of parameters needed to describe the model divided by the number of ob servations most of our examples involve density or regression estimation settings and we focus on the problem of estimating the unknown density or regression function we show that the quadratic risk of the minimum penal ized empirical contrast estimatoris bounded by an index of the accuracy of the sieve this accuracy index quanties the trade off among the candidate models between the approximation error and parameter dimension relative to sample size if we choose a list of models which exhibit good approximation prop erties with respect to different classes of smoothness the estimator can be simultaneously minimax rate optimal in each of those classes this is what is usually called adaptation the type of classes of smoothness in which one gets adaptation depends heavily on the list of models if too many models are involved in order to get accurate approximation of many wide classes of functions simultaneously it may happen that the estimator is only approx

structural break estimation for nonstationary time series models this article considers the problem of modeling a class of nonstationary time series using piecewise autoregressive ar processes the number and locations of the piecewise ar segments as well as the orders of the respective ar processes are assumed unknown the minimum description length principle is applied to compare various segmented ar fits to the data the goal is to find the best combination of the number of segments the lengths of the segments and the orders of the piecewise ar processes such a best combination is implicitly defined as the optimizer of an objective function and a genetic algorithm is implemented to solve this difficult optimization problem numerical results from simulation experiments and real data analyses show that the procedure has excellent empirical properties the segmentation of multivariate time series is also considered assuming that the true underlying model is a segmented autoregression this procedure is shown to be consistent for estimating the location of

implicit large eddy simulation of non wall bounded turbulent flows based on the multiscale properties of a high order finite volume method in this paper it is presented the application of a higher order finite volume method based on moving least squares approximations fv mls to the resolution of non wall bounded compressible turbulent flows our approach is based on the monotonically implicit large eddy simulation miles the main idea of miles methodology is the absence of any explicit subgrid scale sgs model in the numerical algorithm to solve turbulent flows in the case of the fv mls method we take advantage of the multiresolution properties of moving least squares approximations and we show that they can be used as an implicit sgs model the numerical results are encouraging the third order fv mls method is able to reproduce the inertial subrange and it obtains better results than other usual numerical schemes in les computations such as the muscl scheme we note that in the present state of this research the numerical method is not yet suited for wall bounded flows this paper is the first step in the application of the fv mls method to general turbulent flows

design selection and classification for hadamard matrices using generalized minimum aberration criteria deng and tang 1999 and tang and deng 1999 proposed and justified two criteria of generalized minimum aberration for general two level fractional factorial designs the criteria are defined using a set of values called j characteristics in this article we examine the practical use of the criteria in design selection specifically we consider the problem of classifying and ranking designs that are based on hadamard matrices a theoretical result on j characteristics is developed to facilitate the computation the issue of design selection is further studied by linking generalized aberration with the criteria of efficiency and estimation capacity our studies reveal that generalized aberration performs quite well under these familiar criteria

large eddy simulation of high reynolds number free and wall bounded flows the ability to simulate complex unsteady flows is limited by the current state of the art of subgrid scale sgs modeling which invariably relies on the use of smagorinsky type isotropic eddy viscosity models turbulent flows of practical importance involve inherently three dimensional unsteady features often subjected to strong inhomogeneous effects and rapid deformation which cannot be captured by isotropic models although some available improved sgs models can outperform the isotropic eddy viscosity models their practical use is typically limited because of their complexity development of more sophisticated sgs models is actively pursued and it is desirable to also investigate alternative nonconventional approaches in ordinary large eddy simulation les approaches models are introduced for closure of the low pass filtered navier strokes equations nse a promising les approach is the monotonically integrated les miles which involves solving the unfiltered nse using high resolution monotone algorithms in this approach implicit sgs models provided by intrinsic nonlinear high frequeacy filters built into the convection discretization are coupled naturally to the resolvable scales of the flow formal properties of the effective sgs modeling using miles are documented using databases of simulated free and wall bounded inhomogeneous flows including isotropic decaying turbulence transitional jets and channel flows mathematical and physical aspects of implicit sgs modeling through the use of nonlinear flux limiters are addressed using a formalism based on the modified les equations

wavelet thresholding in anisotropic function classes and application to adaptive estimation of evolutionary spectra we derive minimax rates for estimation in anisotropic smoothness classes this rate is attained by a coordinatewise thresholded wavelet estimator based on a tensor product basis with separate scale parameter for every dimension it is shown that this basis is superior to its one scale multiresolution analog if different degrees of smoothness in different directions are present as an important application we introduce a new adaptive wavelet estimator of the time dependent spectrum of a locally stationary time series using this model which was resently developed by dahlhaus we show that the resulting estimator attains nearly the rate which is optimal in gaussian white noise simultaneously over a wide range of smoothness classes moreover by our new approach we overcome the difficulty of how to choose the right amount of smoothing i e how to adapt to the appropriate resolution for reconstructing the local structure of the evolutionary spectrum in the time frequency plane

implicit large eddy simulation of swept wing flow using high resolution methods a numerical investigation of a fully three dimensional swept wing geometry featuring separation from a curved leading edge is presented the implicit large eddy simulation strategy based on a third order high resolution method for discretizing the advective fluxes and a second order runge kutta time stepping scheme with an extended stability region have been employed no attempt to incorporate a wall model has been made instead the boundary layer is fully resolved over the majority of the wing qualitative and quantitative comparisons with experimental oil film visualizations and three dimensional laser doppler anemometry measurements show very good agreement between the experiment and the numerically predicted flow structures as well as velocity and stress profiles near the wing furthermore data from a hybrid reynolds averaged navier stokes and large eddy simulation have been included for comparison

interactions of breaking waves with a current over cut cells by design of the external and internal wave current generators the objective of this paper is to extend our efficient navier stokes solver t li p troch j de rouck wave overtopping over a sea dike j comput phys 198 2004 686 726 for modelling of interactions between breaking waves and a current over a cut cell grid based on a dynamic subgrid scale sgs model this solver is constructed by a novel vof finite volume approach coupled with surface tension when studying waves following a positive current our external generator creates the combined inflow motions of waves and a current which is viewed as one type of wavy inflow conditions for cases of waves against strong currents our internal generator describes the opposing current by incorporating the source function to the continuity and momentum equations as a net driving force acting on the fluid elements lying within the finite thickness source region the outgoing waves downstream are dissipated with a breaking type wave absorber placed in the tank extremity five test cases recommended are of distinctly different applications of interest characterized by overtopping of following waves over sloping and vertical structures under the grid refinement effects the results in 2d and 3d are in close agreement with the experimental data available in terms of the surface wave additionally the performance of convergence in computations is also investigated including full discussion for waves on beaches between 2d and 3d by visualization of the motions that describe the physics of turbulence it has been shown that our solver can capture most of the significant features in wave current interactions varying with three different current speeds positive zero negative

reduced order structure of reacting rectangular jets the results of proper orthogonal decomposition analyses on co 2 number density and vorticity magnitude data from reacting rectangular jet simulations are presented the resulting proper orthogonal decomposition eigenfunctions are used to develop physical insight of the vortex formations and dynamics of these jets and their related mixing and spreading characteristics it is seen that different vortex structures are captured in the eigenfunctions and that co 2 and vorticity eigenfunctions are very similar indicating that vortex driven mixing dominates in these jets the eigenvalue spectra associated with these eigenfunctions are used to evaluate the information content of the eigenfunctions and the potential for reduced order models using subsets of eigenfunctions with high information content co 2 and vorticity magnitude distributions can be represented with relatively few eigenfunctions however as the flows develop downstream more eigenfunctions are needed to represent them to the same level of accuracy the potential for reduced order modeling of each field is approximately the same for the jets of aspect ratios 1 2 and 3 however there is stronger potential for reduced order modeling of the co 2 field than of the vorticity field

geophysical astrophysical spectral element adaptive refinement gaspar object oriented h adaptive fluid dynamics simulation an object oriented geophysical and astrophysical spectral element adaptive refinement gaspar code is introduced like most spectral element codes gaspar combines finite element efficiency with spectral method accuracy it is also designed to be flexible enough for a range of geophysics and astrophysics applications where turbulence or other complex multiscale problems arise the formalism accommodates both conforming and non conforming elements several aspects of this code derive from existing methods but here are synthesized into a new formulation of dynamic adaptive refinement dare of non conforming h type as a demonstration of the code several new 2d test cases are introduced that have time dependent analytic solutions and exhibit localized flow features including the 2d burgers equation with straight curved radial and oblique colliding fronts these are proposed as standard test problems for comparable dare codes quantitative errors are reported for 2d spatial and temporal convergence of dare

adaptive estimation in autoregression or mixing regression via model selection we study the problem of estimatingsome unknown regression function in a beta mixing dependent framework to this end we consider some collection of models which are finite dimensional spaces a penalized least squares estimator plse is built on a data driven selected model among this collection we state non asymptotic risk bounds for this plse and give several examples where the procedure can be applied autoregression regression with arithmetically beta mixing design points regression with mixing errors estimation in additive frameworks estimation of the order of the autoregression in addition we show that under a weak moment condition on the errors our estimator is adaptive in the minimax sense simultaneously over some family of besov balls

an application of a hill based response surface model for a drug combination experiment on lung cancer combination chemotherapy with multiple drugs has been widely applied to cancer treatment owing to enhanced efficacy and reduced drug resistance for drug combination experiment analysis response surface modeling has been commonly adopted in this paper we introduce a hill based global response surface model and provide an application of the model to a 512 run drug combination experiment with three chemicals namely ag490 u0126 and indirubin 3 monoxime i 3 m on lung cancer cells the results demonstrate generally improved goodness of fit of our model from the traditional polynomial model as well as the original hill model on the basis of fixed ratio drug combinations we identify different dose effect patterns between normal and cancer cells on the basis of our model which indicates the potential effectiveness of the drug combination in cancer treatment meanwhile drug interactions are analyzed both qualitatively and quantitatively the distinct interaction patterns between u0126 and i 3 m on two types of cells uncovered by the model could be a further indicator of the efficacy of the drug combination copyright 2014 john wiley sons ltd

measures of intermittency in driven supersonic flows scaling exponents for structure functions of the velocity density and entropy are computed for driven supersonic flows for rms mach numbers of order unity with numerical simulations using the piecewise parabolic method algorithm on grids of up to 512 3 points the driving is made up of either one or three orthogonal shear waves in all cases studied the compressible component of the velocity in the statistically steady regime is weaker than its solenoidal counterpart by roughly a factor of 6 exponents for the longitudinal component of the velocity are comparable to what is found in the incompressible case and appear insensitive to the presence of numerous shocks scaling exponents of the transverse components of the velocity are comparable to those for the longitudinal component density and entropy structure functions display strong departures from linear scaling finally the scaling of structure functions of the energy transfer is also given and compared with the kolmogorov refined similarity hypothesis

two level designs to estimate all main effects and two factor interactions we study the design of two level experiments with n runs and n factors large enough to estimate the interaction model which contains all the main effects and all the two factor interactions yet an effect hierarchy assumption suggests that main effect estimation should be given more prominence than the estimation of two factor interactions orthogonal arrays oas favor main effect estimation however complete enumeration becomes infeasible for cases relevant for practitioners we develop a partial enumeration procedure for these cases and we establish upper bounds on the d efficiency for the interaction model based on arrays that have not been generated by the partial enumeration we also propose an optimal design procedure that favors main effect estimation designs created with this procedure have smaller d efficiencies for the interaction model than d optimal designs but standard errors for the main effects in this model are improved generated oas for 7 10 factors and 32 72 runs are smaller or have a higher d efficiency than the smallest oas from the literature designs obtained with the new optimal design procedure or strength 3 oas which have main effects that are not correlated with two factor interactions are recommended if main effects unbiased by possible two factor interactions are of primary interest d optimal designs are recommended if interactions are of primary interest supplementary materials for this article are available online 2017 american statistical association and the american society for quality

a note on foldover of 2k p designs with column permutations foldover is a commonly used follow up strategy in experimental designs all existing foldover designs were constructed by reversing the sign of columns of the initial design we propose a new methodology by allowing the permutation of columns in foldover focusing on resolution iv designs we show that almost all designs are better than existing results with respect to the minimum aberration criterion while augmenting a design by a foldover with column permutations may result in a nonregular combined design the proposed designs all have a resolution of 4 5 or higher for which no two factor interaction is fully aliased with any other two factor interactions

construction of maximin distance latin squares and related latin hypercube designs summarymaximin distance latin hypercube designs are widely used in computer experiments yet their construction is challenging based on number theory and finite fields we propose three algebraic methods to construct maximin distance latin squares as special latin hypercube designs we develop lower bounds on their minimum distances the resulting latin squares and related latin hypercube designs have larger minimum distances than existing ones and are especially appealing for high dimensional applications

fitting time series models to nonstationary processes a general minimum distance estimation procedure is presented for nonstationary time series models that have an evolutionary spectral representation the asymptotic properties of the estimate are derived under the assumption of possible model misspecification for autoregressive processes with time varying coefficients the estimate is compared to the least squares estimate furthermore the behavior of estimates is explained when a stationary model is fitted to a nonstationary process

convergence tests for the piecewise parabolic method and navier stokes solutions for homogeneous compressible turbulence the need to simulate fully developed turbulence with wide range of scales led us to use the piecewise parabolic method ppm to solve the euler equations of motions to obtain data for 3 d homogeneous compressible decaying turbulence numerical simulations were performed on computational meshes of up to 10243 zones these data were compared with data obtained by solving the navier stokes ns equations results of studying the kinetic energy enstrophy and the energy power spectra with different resolutions are presented for both the ppm and ns data the results of the comparison show convergence of the ppm and ns solutions to the same limit

construction of two level nonregular designs of strength three with large run sizes abstracttwo level orthogonal arrays of strength 3 permit the study of the main effects and the two factor interactions of the experimental factors these arrays are classified into regular and nonr

on recursive estimation for time varying autoregressive processes this paper focuses on recursive estimation of time varying autoregressive processes in a nonparametric setting the stability of the model is revisited and uniform results are provided when the time varying autoregressive parameters belong to appropriate smoothness classes an adequate normalization for the correction term used in the recursive estimation procedure allows for very mild assumptions on the innovations distributions the rate of convergence of the pointwise estimates is shown to be minimax in lipschitz classes for 0 1 for 1 2 this property no longer holds this can be seen by using an asymptotic expansion of the estimation error a bias reduction method is then proposed for recovering the minimax rate

the coordinate exchange algorithm for constructing exact optimal experimental designs we describe the cyclic coordinate exchange algorithm for constructing d optimal and linear optimal experimental designs the algorithm uses a variant of the gauss southwell cyclic coordinate descent algorithm within the k exchange algorithm to achieve substantive reductions in required computing among its advantages are the following candidate sets which grow exponentially in the number of factors need not be explicitly constructed or enumerated convex design spaces or mixed convex by discrete design spaces are handled directly without the need for sophisticated nonlinear programming routines or candidate set adjustment for design problems having 10 or more factors the reductions in execution time are typically two or more orders of magnitude when compared to standard candidateset based procedures such as k exchange yet the designs produced exhibit no loss of efficiency

semiparametric model building for regression models with time varying parameters abstract this paper considers the problem of semiparametric model building for linear regression models with potentially time varying coefficients by allowing the response variable and explanatory variables be jointly a nonstationary process the proposed methods are widely applicable to nonstationary and dependent observations we propose a local linear shrinkage method that can simultaneously achieve parameter estimation and variable selection its selection consistency and the favorable oracle property are established due to the fear of losing efficiency an information criterion is further proposed for distinguishing between time varying and time constant components numerical examples are presented to illustrate the proposed methods

flux corrected transport this paper describes a class of explicit eulerian finite difference algorithms for solving the continuity equation which are built around a technique called flux correction these flux corrected transport fct algorithms are of indeterminate order but yield realistic accurate results in addition to the mass conserving property of most conventional algorithms the fct algorithms strictly maintain the positivity of actual mass densities so steep gradients and inviscid shocks are handled particularly well this first paper concentrates on a simple one dimensional version of fct utilizing shasta a new transport algorithm for the continuity equation which is described in detail

numerical comparison of riemann solvers for astrophysical hydrodynamics the idea of this work is to compare a new positive and entropy stable approximate riemann solver by francois bouchut with a state of the art algorithm for astrophysical fluid dynamics we implemented the new riemann solver into an astrophysical ppm code the prometheus code and also made a version with a different more theoretically grounded higher order algorithm than ppm we present shock tube tests two dimensional instability tests and forced turbulence simulations in three dimensions we find subtle differences between the codes in the shock tube tests and in the statistics of the turbulence simulations the new riemann solver increases the computational speed without significant loss of accuracy

a subgrid scale deconvolution approach for shock capturing we develop a method for the modeling of flow discontinuities which can arise as weak solutions of inviscid conservation laws due to its similarity with recently proposed approximate deconvolution models for large eddy simulation the method potentially allows for a unified treatment of flow discontinuities and turbulent subgrid scales a filtering approach is employed since for the filtered evolution equations the solution is smooth and can be solved for by standard central finite difference schemes without special consideration of discontinuities a sufficiently accurate representation of the filtered nonlinear combination of discontinuous solution components which arise from the convection term can be obtained by a regularized deconvolution applied to the filtered solution for stable integration the evolution equations are supplemented by a relaxation regularization based on a secondary filter operation and a relaxation parameter an estimate for the relaxation parameter is provided the method is related to the spectral vanishing viscosity method and the regularized chapman enskog expansion method for conservation laws we detail the approach and demonstrate its efficiency with the inviscid and viscous burgers equations the isothermal shock problem and the one dimensional euler equations

semiparametric estimation by model selection for locally stationary processes over recent decades increasingly more attention has been paid to the problem of how to fit a parametric model of time series with time varying parameters a typical example is given by autoregressive models with time varying parameters we propose a procedure to fit such time varying models to general non stationary processes the estimator is a maximum whittle likelihood estimator on sieves the results do not assume that the observed process belongs to a specific class of time varying parametric models we discuss in more detail the fitting of time varying ar p processes for which we treat the problem of the selection of the order p and we propose an iterative algorithm for the computation of the estimator a comparison with model selection by akaike s information criterion is provided through simulations

local inference for locally stationary time series based on the empirical spectral measure abstract the time varying empirical spectral measure plays a major role in the treatment of inference problems for locally stationary processes the properties of the empirical spectral measure and related statistics are studied both when its index function is fixed or when dependent on the sample size in particular we prove a general central limit theorem several applications and examples are given including semiparametric whittle estimation local least squares estimation and spectral density estimation