recursive nonparametric identification of nonlinear systems with adaptive binary sensors in this paper the problem of identifying nonlinear systems under adaptive binary valued output measurements is considered we follow a nonparametric approach which directly estimates the value of the nonlinear function representing the system at any fixed point with the help of a recursive kernel based stochastic approximation algorithm with expanding truncations saawet the thresholds of the binary sensor are adaptively designed to achieve a sufficient richness of information in the output observations the constructed estimates are proved to converge to the true values with probability one two numerical examples are given showing that the simulation results are consistent with the theoretical analysis

statistical analysis of multiple sociometric relations abstract loglinear models are adapted for the analysis of multivariate social networks a set of sociometric relations among a group of actors models that focus on the similarities and differences between the relations and models that concentrate on individual actors are discussed this approach allows for the partitioning of the actors into blocks or subgroups some ideas for combining these models are described and the various models and computational methods are applied to the analysis of data for a corporate interlock network of the 25 largest organizations in minneapolis st paul and for a classic network of 18 monks in a cloister the computational techniques all involve variations on the standard iterative proportional fitting algorithm used extensively in the analysis of multidimensional contingency tables

kernel based approaches to local nonlinear non parametric variable selection in this paper we consider the variable selection problem for a nonlinear non parametric system two approaches are proposed one top down approach and one bottom up approach the top down algorithm selects a variable by detecting if the corresponding partial derivative is zero or not at the point of interest the algorithm is shown to have not only the parameter but also the set convergence this is critical because the variable selection problem is binary a variable is either selected or not selected the bottom up approach is based on the forward backward stepwise selection which is designed to work if the data length is limited both approaches determine the most important variables locally and allow the unknown non parametric nonlinear system to have different local dimensions at different points of interest further two potential applications along with numerical simulations are provided to illustrate the usefulness of the proposed algorithms

identification of hammerstein systems with quantized observations this work is concerned with identification of hammerstein systems whose outputs are measured by quantized sensors the system consists of a memoryless nonlinearity that is polynomial and possibly noninvertible followed by a linear subsystem the parameters of linear and nonlinear parts are unknown but have known orders input design identification algorithms and their essential properties are presented under the assumptions that the distribution function of the noise is known and the quantization thresholds are known the concept of strongly scaled full rank signals is introduced to capture the essential conditions under which the hammerstein system can be identified with set valued observations under strongly scaled full rank conditions a strongly convergent algorithm is constructed asymptotic consistency and efficiency of the algorithm are investigated

three dimensional multigrid reynolds averaged navier stokes solver for unstructured meshes turbulence is simulated using a single field equation model computational overheads are minimized through the use of a single edge based data structure an efficient multigrid solution technique and the use of multitasking on shared memory multiprocessors the accuracy and efficiency of the code are evaluated by computing two dimensional flows in three dimensions and comparing with results from a previously validated two dimensional code that employs the same solution algorithm the feasibility of computing three dimensional turbulent flows on grids or several million points in less than 2 h of wall clock time is demonstrated

a modified nodal scheme for the time dependent incompressible navier stokes equations based on poisson equation for pressure a nodal numerical scheme is developed for the time dependent incompressible navier stokes equations derivation is based on local transverse integrations over finite size brick like cells that transform each partial differential equation to a set of ordinary differential equations odes solutions of these odes for the transverse averaged dependent variables are then utilized to develop the difference scheme the discrete variables are scalar velocities and pressure averaged over the faces of brick like cells in the x y t space cell interior variation of transverse averaged pressure in each spatial direction is quadratic cell interior variation of transverse averaged velocity in each spatial direction is a sum of a constant a linear and an exponential term due to the introduction of delayed coefficients the exponential functions are to be evaluated only once at each time step the semi implicit scheme has inherent upwinding results of applications to several test problems show that the scheme is very robust and leads to a second order error as expected in such coarse mesh schemes even relatively large size cells lead to small errors extension to three dimensions is straightforward

nonlinear system identification via direct weight optimization a general framework for estimating nonlinear functions and systems is described and analyzed in this paper identification of a system is seen as estimation of a predictor function the considered predictor function estimate at a particular point is defined to be affine in the observed outputs and the estimate is defined by the weights in this expression for each given point the maximal mean square error or an upper bound of the function estimate over a class of possible true functions is minimized with respect to the weights which is a convex optimization problem this gives different types of algorithms depending on the chosen function class it is shown how the classical linear least squares is obtained as a special case and how unknown but bounded disturbances can be handled most of the paper deals with the method applied to locally smooth predictor functions it is shown how this leads to local estimators with a finite bandwidth meaning that only observations in a neighborhood of the target point will be used in the estimate the size of this neighborhood the bandwidth is automatically computed and reflects the noise level in the data and the smoothness priors the approach is applied to a number of dynamical systems to illustrate its potential

an implicit explicit hybrid method for lagrangian hydrodynamics abstract we describe a new implicit explicit hybrid method for solving the equations of hydrodynamics the scheme is an extension of the explicit second order piecewise parabolic method ppm which is unconditionally stable the scheme is thus of the godunov type it is conservative accurate to second order in both space and time and makes use of a nonlinear riemann solver to obtain fluxes of the conserved quantities the hybrid character of the method provides increased accuracy and computational efficiency switching between implicit and explicit formulations occurs smoothly and in a natural way and is performed separately for each characteristic family of waves the method provides high resolution with shocks spread over only one zone and can produce accurate answers to most reasonable problems without the use of an artificial viscosity 1986 academic press inc

efficient solution algorithms for the riemann problem for real gases a procedure for constructing solutions to the riemann problem for gas dynamics with a general convex equation of state is given approximate procedures involving a local parametrization of the equation of state are introduced in order to calculate numerical fluxes in conservative finite difference schemes this leads to difference schemes which are as accurate and almost as fast as the analogous schemes for polytropic gases numerical results in one and two space variables are presented

large eddy simulation in complex geometric configurations using boundary body forces anumericalmethodispresentedthatallowslargeeddysimulation les ofturbulente owsincomplexgeometric cone gurations with moving boundaries and that retains the advantages of solving the navier stokes equations on e xed orthogonal grids the boundary conditions are applied independently of the grid by assigning body forces over surfaces that need not coincide with coordinate lines the use of orthogonal nondeforming grids simplie es grid generation facilitates theimplementation of high order nondissipativediscretization schemes andminimizes the spatial and temporal variations in e lter width that complicate unstructured deforming grid les dynamic subgrid scaleturbulence models areparticularly appealing in combination with the body forceprocedure because the dynamic model accounts automatically for the presence of solid walls without requiring damping functions the method is validated by simulations of the turbulent e ow in a motored axisymmetric piston cylinder assembly for which detailed experimental measurements are available computed mean and rms velocity proe les show very good agreement with measured ensemble averages thepresent numerical code runs on small personal computerlike workstations for a comparable level of accuracy computational requirements memory and cpu time are at least a factor of 10 lower compared to published simulations for the same cone guration obtained using an unstructured boundary e tted deforming grid approach

mesh independent spectra in the moving finite element equations we derive the moving finite element mfe equations for the solution of a scalar evolutionary equation in d space dimensions d geqq 1 and introduce the elementwise approach to mfe this approa

asymptotic properties of sign algorithms for adaptive filtering this paper develops asymptotic properties of a class of sign error algorithms with expanding truncation bounds for adaptive filtering under merely stationary ergodicity and finite second moments of the reference and output signals and using trajectory subsequence ts method it is proved that the algorithm convergers almost surely then a mean squares estimate is derived for the estimation error and a suitably scaled sequence of the estimation error is shown to converge to a diffusion process the scaling factor together with the stationary covariance gives the rate of convergence result moreover an algorithm under mean squares criterion with expanding truncation bounds is also examined compared with the existing results in the literature sufficient conditions for almost sure convergence are much relaxed a simple example is provided for demonstration purpose

recursive identification for nonlinear arx systems based on stochastic approximation algorithm the nonparametric identification for nonlinear autoregressive systems with exogenous inputs narx described by yk 1 f yk yk 1 n0 uk uk 1 n0 ek 1 is considered first a condition on f is introduced to guarantee ergodicity and stationarity of yk then the kernel function based stochastic approximation algorithm with expanding truncations saawet is proposed to recursively estimate the value of f at any given y 1 y n0 u 1 u n0 r2n0 it is shown that the estimate converges to the true value with probability one in establishing the strong consistency of the estimate the properties of the markov chain associated with the narx system play an important role numerical examples are given which show that the simulation results are consistent with the theoretical analysis the intention of the paper is not only to present a concrete solution to the problem under consideration but also to profile a new analysis method for nonlinear systems the proposed method consisting in combining the markov chain properties with stochastic approximation algorithms may be of future potential although a restrictive condition has to be imposed on f that is the growth rate of f x should not be faster than linear with coefficient less than 1 as x tends to infinity

temporal adaptive euler navier stokes algorithm involving unstructured dynamic meshes a temporal adaptive algorithm for the time integration of the two dimensional euler or navier stokes equations is presented the flow solver involves an upwind flux split spatial discretization for the convective terms and central differencing for the shear stress and heat flux terms on an unstructured mesh of triangles the temporal adaptive algorithm is a time accurate integration procedure that allows flows with high spatial and temporal gradients to be computed efficiently by advancing each grid cell near its maximum allowable time step

a maximum principle satisfying modification of triangle based adaptive stencils for the solution of scalar hyperbolic conservation laws a modified triangle based adaptive difference stencil for the numerical approximation of scalar hyperbolic conservation laws in two space dimensions is constructed the scheme satisfies the maximum principle and approximates the flux with second order accuracy

stochastic blockmodels for directed graphs abstract holland and leinhardt 1981 proposed the p 1 model for the analysis of binary directed graph data in network studies such a model provides information about the attractiveness and expansiveness of the individual nodes in the network as well as the tendency of a pair of nodes to reciprocate relational ties when the nodes are a priori partitioned into subgroups based on attributes such as race and sex the density of ties from one subgroup to another can differ considerably from that relating another pair of subgroups thus creating a situation called blocking in social networks the p 1 model completely ignores this extra piece of information and is therefore unable to explain the block structure blockmodels that are simple extensions of the p 1 model are proposed specifically for such data an iterative scaling algorithm is presented for fitting the model parameters by maximum likelihood the methodology is illustrated in detail on two empirical examples

time integration algorithms for the two dimensional euler equations on unstructured meshes explicit and implicit time integration algorithms for the two dimensional euler equations on unstructured grids are presented both cell centered and cell vertex finite volume upwind schemes utilizing roe s approximate riemann solver are developed for the cell vertex scheme a four stage runge kutta time integration a four stage runge kutta time integration with implicit residual averaging a point jacobi method a symmetric point gauss seidel method and two methods utilizing preconditioned sparse matrix solvers are presented for the cell centered scheme a runge kutta scheme an implicit tridiagonal relaxation scheme modeled after line gaussseidel a fully implicit lower upper lu decomposition and a hybrid scheme utilizing both runge kutta and lu methods are presented

a recursive local linear estimator for identification of nonlinear arx systems asymptotical convergence and applications in this paper we propose a recursive local linear estimator rlle for nonparametric identification of nonlinear autoregressive systems with exogenous inputs narx first the rlle is introduced next the strong consistency as well as the asymptotical mean square error properties of the rlle are established and then an application of the rlle to an additive nonlinear system is discussed the rlle provides recursive estimates not only for the function values but also their gradients at fixed points a simulation example is provided to confirm the theoretical analysis

input design in worst case system identification using binary sensors this technical note addresses system identification using binary valued sensors in a worst case set membership setting the main contribution is the solution of the optimal input design problem for identification of scalar gains which is instrumental to the construction of suboptimal input signals for identification of fir models of arbitrary order two different cost functions are considered for input design the maximum parametric identification error and the relative uncertainty reduction with respect to the minimum achievable error it is shown that in the latter case the solution enjoys the property of being independent of the length of the identification experiment and as such it can be implemented as an optimal recursive procedure over a time interval of arbitrary length

discrete adjoint based approach for optimization problems on three dimensional unstructured meshes a comprehensive strategy for developing and implementing discrete adjoint methods for aerodynamic shape optimization problems is presented by linearizing each procedure in the entire optimization problem transposing each linearization and reversing the sequential order of operations the adjoint of the complete optimization problem including flow equations and mesh motion equations is constructed in a modular and verifiable fashion this construction is also shown to produce minimal memory overheads and retain the same convergence characteristics of the original analysis problem in the sensitivity analysis these techniques are implemented in a three dimensional unstructured multigrid navierstokes solver and demonstrated on a transonic drag reduction problem for a wing body configuration

high re solutions for incompressible flow using the navier stokes equations and a multigrid method the vorticity stream function formulation of the two dimensional incompressible navierstokes equations is used to study the effectiveness of the coupled strongly implicit multigrid csi mg method in the determination of high re fine mesh flow solutions the driven flow in a square cavity is used as the model problem solutions are obtained for configurations with reynolds number as high as 10 000 and meshes consisting of as many as 257 x 257 points for re 1000 the 129 x 129 grid solution required 1 5 minutes of cpu time on the amdahl 470 v 6 computer because of the appearance of one or more secondary vortices in the flow field uniform mesh refinement was preferred to the use of one dimensional gridclustering coordinate transformations the past decade has witnessed a great deal of progress in the area of computational fluid dynamics developments in computer technology hardware as well as in advanced numerical algorithms have enabled attempts to be made towards analysis and numerical solution of highly complex flow problems for some of these applications the use of simple iterative techniques to solve the navier stokes equations leads to a rather slow convergence rate for the solutions the solution convergence rate can be seriously affected if the coupling among the various governing differential equations is not properly honored either in the interior of the solution domain or at its boundaries the rate of convergence is also generally strongly dependent on such problem parameters as the reynolds number the mesh size and the total number of computational points this has led several researchers to examine carefully the recently emerging multigrid mg technique as a useful means for enhancing the convergence rate of iterative numerical methods for solving discretized equations at a number of computational grid points so large as to be considered impractical previously

a general framework for nonparametric identification of nonlinear stochastic systems in this paper nonparametric identification of nonlinear autoregressive systems with exogenous inputs narx is considered a general criterion function is introduced for estimating the value of the nonlinear function within the system at any fixed point the criterion function is constructed using a kernel together with a convex objective function not only does this framework include the classical kernel based weighted least squares estimator but also the kernel based l q q geq1 criteria as special cases first we prove that the minimizer of the general criterion function converges to the true function value with probability one second recursive algorithms are proposed to find the estimates which minimize the criterion function and it is shown that these estimates also converge to the true function value with probability one numerical examples are given justifying that the framework guarantees the strong consistency of the estimates and exhibits the robustness against outliers in the observations

unsteady transonic two dimensional euler solutions using finite elements a finite element solution of the unsteady euler equations is presented and demonstrated for two dimensional airfoil configurations oscillating in transonic flows computations are performed by spatially discretizing the conservation equations using the galerkin weighted residual method and then employing a multistage rungekutta scheme to march forward in time triangular finite elements are employed in an unstructured o mesh computational grid surrounding the airfoil grid points are fixed in space at the far field boundary and are constrained to move with the airfoil surface to form the near field boundary a mesh deformation scheme has been developed to efficiently move interior points in a smooth fashion as the airfoil undergoes rigid body pitch and plunge motion both steady and unsteady results are presented and a comparison is made with solutions obtained using finite volume techniques the effects of using either a lumped or consistent mass matrix were studied and are presented results show the finite element method provides an accurate solution for unsteady transonic flows about isolated airfoils he accurate determination of the unsteady flowfield surrounding an oscillating airfoil or wing in transonic flow is of paramount importance in the prediction of the flutter characteristics of the body transonic flutter remains an active research topic because of the continued interest by both the military and commercial sectors to operate in these flight regimes with vehicles that are ever lighter and as a result more flexible typically analysis of fluid structure interaction in flight vehicles involves describing the vehicle structure using finite elements whereas finite difference methods are used to model the surrounding fluid coupling of the two dissimilar models then presents problems because of the disparity between the two solution techniques additional complexities arise because of phase mismatching between the fluid pressures and the displacements of the structure it seems a natural progression to use finite element methods to describe the behavior of both the fluid and structure thus bringing more commonality into the analysis of the two media early research efforts concentrated on using the transonic small disturbance equation or the nonlinear full potential equation as the model for the gas dynamic behavior in transonic flows unfortunately this idealization leads to errors when strong shocks are present because of their inability to account for the production of entropy and vorticity to properly account for these effects within the framework of the conservation laws the euler equations must be used these equations although they neglect fluid viscosity have become the standard when unsteady transonic solutions are desired the absence of a viscosity representation is an important limitation of the present formulation and must be considered

representation and identification of non parametric nonlinear systems of short term memory and low degree of interaction in this paper we propose a new representation which is particularly useful for a class of non parametric nonlinear systems that have short term memory and low degree of interaction advantages and disadvantages of this representation are discussed and compared to existing methods both theoretically and numerically furthermore results regarding structural estimation based on the analysis of variance and on full scale identification are also provided

convergence analysis of the gauss seidel preconditioner for discretized one dimensional euler equations we consider the nonlinear system of equations that results from the van leer flux vector splitting discretization of the one dimensional euler equations this nonlinear system is linearized at the discrete solution the main topic of this paper is a convergence analysis of block gauss seidel methods applied to this linear system of equations both the lexicographic and the symmetric block gauss seidel method are considered we derive results which quantify the quality of these methods as preconditioners these results show for example that for the subsonic case the symmetric gauss seidel method can be expected to be a much better preconditioner than the lexicographic variant sharp bounds for the condition number of the preconditioned matrix are derived

conjugate gradient like algorithms for solving nonsymmetric linear systems this paper presents a unified formulation of a class of the conjugate gradient like algorithms for solving nonsymmetric linear systems the common framework is the petrov galerkin method on krylov subspaces we discuss some practical points concerning the methods and point out some of the interrelations between them 1 introduction in the recent few years a large number of generalizations of the conjugate gradient and conjugate residual methods which are very successful in solving symmetric positive definite linear systems have been proposed for solving nonsymmetric linear systems 3 6 5 7 12 in this paper we present an abstract framework which includes most of these methods and many new ones our goal is to understand the relationships among the methods and to synthesize consider the general linear system

convergence and logarithm laws of self tuning regulators abstract this paper starts with a survey of some recent results on least squares ls and ls based self tuning regulators str several long standing problems concerning the basic properties of ls based str such as stability optimality consistency and the best convergence rate are solved within a unified framework some previously related results are also subsumed and extended various new techniques for analysing ls based adaptive tracking systems are presented which may also be useful for analysing other adaptive control problems

finite data rate feedback stabilization of switched and hybrid linear systems we study the problem of asymptotically stabilizing a switched linear control system using sampled and quantized measurements of its state the switching is assumed to be slow enough in the sense of combined dwell time and average dwell time each individual mode is assumed to be stabilizable and the available data rate is assumed to be large enough but finite our encoding and control strategy is rooted in the one proposed in our earlier work on non switched systems and in particular the data rate bound used here is the data rate bound from that earlier work maximized over the individual modes the main technical step that enables the extension to switched systems concerns propagating over approximations of reachable sets through sampling intervals during which the switching signal is not known a novel algorithm is developed for this purpose our primary focus is on systems with time dependent switching switched systems but the setting of state dependent switching hybrid systems is also discussed

on the mass matrix spectrum bounds of wathen and the local moving finite elements of baines andrew wathen has shown that the eigenvalues of the diagonally preconditioned piecewise linear moving finite element mfe or finite element fe mass matrix in n dimensions lie in frac 1 2 1 frac 1 2 n baines using similar considerations has designed very local mfe methods with block diagonal mass matrices in this paper a simplified proof of wathen s basic spectrum bound is given it results from a simple comparison bound between the l 2 norm and a certain diagonal norm for discontinuous piecewise linear functions on an arbitrary triangular grid the simplicity of our comparison lets us extend wathen s result to other situations such as miller s gradient weighted mfe method gwmfe it also lets us design very local mfe and fe and gwmfe methods which minimize the pde residual dot u l u not in l 2 norm but in a comparable norm these methods turn out to be equivalent to those of baines these methods retain the desired conservation properties for pde s in conservation l

a variable explicit implicit numerical method for calculating advection on unstructured meshes a variable explicit implicit numerical method is presented for calculating fluid advection on hybrid unstructured meshes the method is intended for unsteady flows that have a large range of advective time scales with subregions where the flow may be quasi steady on time scales of interest the method generalizes the method of collins collela and glaz by providing an explicit to implicit switching criterion that is suitable for use on unstructured meshes no directional splitting is used upwinding is in the direction of the material velocity and thus we define and use a new multidimensional limited gradient that generalizes van leer s muscl limiting 7 after reviewing the one dimensional method of collins collela and glaz we present the generalization to hybrid unstructured grids and detail the results of four example calculations that demonstrate the accuracy and flexibility of the new method

implicit method for the computation of unsteady flows on unstructured grids an implicit method for the computation of unsteady flows on unstructured grids is presented following a finite difference approximation for the time derivative the resulting nonlinear system of equations is solved at each time step by using an agglomeration multigrid procedure the method allows for arbitrarily large time steps and is efficient in terms of computational effort and storage inviscid and viscous unsteady flows are computed to validate the procedure the issue of the mass matrix which arises with vertex centered finite volume schemes is addressed the present formulation allows the mass matrix to be inverted indirectly a mesh point movement and reconnection procedure is described that allows the grids to evolve with the motion of bodies as an example of flow over bodies in relative motion flow over a multi element airfoil system undergoing deployment is computed

hybrid explicit implicit unconditionally stable scheme for unsteady compressible flows a variable explicit implicit scheme was proposed by collins et al ccg scheme for one dimensional hyperbolic systems by suitable blending of explicit and implicit schemes this approach aims to ensure a maximum norm diminishing mnd property at all courant numbers although proven for linear equations however the ccg scheme fails to maintain this property unconditionally for non linear equations and requires a specific time step restriction the remedy for this limitation of the ccg scheme is shown and a new general method for the design of unconditionally mnd hybrid schemes for nonlinear hyperbolic equations is proposed an extension to the compressible navier stokes equations is also discussed the method is tested and verified by calculation of the burgers equation on a highly stiff nonuniform grid it is also applied to simulate the reflection of a normal shock wave from the end wall of a two dimensional channel which is attended with unsteady viscous interaction processes including shock bifurcation

recursive algorithms for parameter estimation with adaptive quantizer this paper studies a parameter estimation problem of networked linear systems with fixed rate quantization under the minimum mean square error criterion we propose a recursive estimator of stochastic approximation type and derive a necessary and sufficient condition for its asymptotic unbiasedness this motivates to design an adaptive quantizer for the estimator whose strong consistency asymptotic unbiasedness and asymptotic normality are rigorously proved using the newton based and averaging techniques we obtain two accelerated recursive estimators with the fastest convergence speed of o 1 k and exactly evaluate the quantization effect on the estimation accuracy if the observation noise is gaussian an optimal quantizer and the accelerated estimators are co designed to asymptotically approach the minimum cramer rao lower bound all the estimators share almost the same computational complexity as the gradient algorithms with un quantized observations and can be easily implemented finally the theoretical results are validated by simulations

conservative rezoning algorithm for generalized two dimensional meshes a method is presented for transferring a conserved quantity q from one generalized mesh to another when the volumetric density of q is uniform within each cell of the original mesh

fast dynamic grid deformation based on delaunay graph mapping a simple and efficient dynamic grid deformation technique is proposed for computing unsteady flow problems with geometrical deformation relative body movement or shape changes due to aerodynamic optimisation and fluid structure interaction a delaunay graph of the solution domain is first generated which can be moved easily during the geometric dynamic deformation even for very large distortion a one to one mapping between the delaunay graph and the computational grid is maintained during the movement therefore the new computational grid after the dynamic movement can be generated efficiently through the mapping while maintaining the primary qualities of the grid while most dynamic grid deformation techniques are iterative based on the spring analogy the present method is non iterative and much more efficient on the other hand in comparison with dynamic grid techniques based on transfinite interpolation for structured grids it offers both geometric and cell topology flexibility which is crucial for many unsteady flow problems involving geometric deformation and relative motions the method is demonstrated through some typical unsteady flow test cases including a pitching aerofoil in a fixed domain boundary relative movement between multi element aerofoils due to flap deployment for high lift a deformable sphere in a fixed cube and a three dimensional flexible wing with large deformation

godunov type method on non structured meshes for three dimensional moving boundary problems abstract this paper presents a numerical method for the computation of compressible flows in domains whose boundaries move in a well defined predictable manner the method uses the space time formulation by godunov while the discretization is conducted on non structured tetrahedral meshes using roe s approximate riemann solver an implicit time stepping and a muscl type interpolation the computation of the geometrical parameters required to take into account the movement of the boundaries is described examples including the calculation of the flow in the cylinder of an internal combustion engine illustrates the possibilities of the method

solution of the unsteady euler equations using an implicit dual time method an unfactored implicit time marching method for the solution of the unsteady two dimensional euler equations on deforming grids is described the present work is placed into a multiblock framework and e ts into the development of a generally applicable parallel multiblock e ow solver the convective terms are discretized using an upwind total variation diminishing scheme whereas the unsteady governing equations are discretized using an implicit dual time approach the large sparse linear system arising from the implicit time discretization at each pseudotime step is solved efe ciently by using a conjugate gradient type method with a preconditioning based on a block incomplete lower upper factorization results are shown for a series of pitching airfoil test cases selected from the agard aeroelastic cone gurations for the naca 0012 airfoil comparisons with experimental data and previous published results are presented the efe ciency of the method is demonstrated by looking at the effect of a number of numerical parameters such as the conjugate gradient tolerance and the size of the global time step and by carrying out a grid ree nement study finally a demonstration test case forthe williamsairfoil williams b r an exact test case for the plane potential flow about two adjacent lifting aerofoils national physical lab aeronautical research council research memorandum 3717 london 1973 with an oscillating e ap is presented highlighting the capability of the grid deformation technique

dynamic unstructured method for flows past multiple objects in relative motion a new methodology is developed to simulate unsteady flows about objects in relative motion and compute the trajectory of their motion as determined by this flowfield the method couples the fluid dynamics and rigid body dynamics equations to capture the time dependent interference between stationary and moving boundaries the unsteady compressible inviscid euler equations are solved on dynamic unstructured grids by an explicit finite volume upwind method for efficiency the grid adaptation is perfomed within a window around the moving object the eulerian equations of the rigid body dynamics are solved by a runge kutta method in a noninertial frame of reference this dynamic unstructured flow solver is validated by computing the flow past a sinusoidally pitching airfoil and comparing these results with the experimental data the trajectory code is tested by computing the six degree of freedom trajectory of a store separating from a wing using the experimentally determined force and moment fields then comparing with the experimental trajectory finally the overall methodology is used for two two dimensional examples the flow past a pitching and plunging airfoil and the free call of a store after separation from a wing section

an accelerated fully coupled parallel 3d hybrid finite volume fluid structure interaction scheme abstract in this paper we propose a fast parallel 3d fully coupled partitioned hybrid unstructured finite volume fluid structure interaction fsi scheme spatial discretisation is effected via a vertex centred finite volume method where a hybrid nodal elemental strain procedure is employed for the solid in the interest of accuracy for the incompressible fluid a split step algorithm is presented which allows the entire fluid solid system to be solved in a fully implicit yet matrix free manner the algorithm combines a preconditioned gmres solver for implicit integration of pressures with dual timestepping on the momentum equations thereby allowing strong coupling of the system to occur through the inner solver iterations further acceleration is provided at little additional cost by applying lu sgs relaxation to the viscous and advective terms the solver is parallelised for distributed memory systems using mpi and its scaling efficiency evaluated the developed modelling technology is evaluated by application to two 3d fsi problems the advanced matrix free solvers achieve reductions in overall cpu time of up to 50 times while preserving close to linear parallel computing scaling using up to 128 cpus for the problems considered

a weighted least squares approach to parameter estimation problems based on binary measurements we present a new approach to parameter estimation problems based on binary measurements motivated by the need to add integrated low cost self test features to microfabricated devices this approach is based on the use of original weighted least squares criteria as opposed to other existing methods it requires no dithering signal and it does not rely on an approximation of the quantizer in this technical note we focus on a simple choice for the weights and establish some asymptotical properties of the corresponding criterion to achieve this the assumption that the quantizer s input is gaussian and centered is made in this context we prove that the proposed criterion is locally convex and that it is possible to use a simple gradient descent to find a consistent estimate of the unknown system parameters regardless of the presence of measurement noise at the quantizer s input

kernel based local order estimation of nonlinear nonparametric systems we consider the local order estimation of nonlinear autoregressive systems with exogenous inputs narx which may have different local dimensions at different points by minimizing the kernel based local information criterion introduced in this paper the strongly consistent estimates for the local orders of the narx system at points of interest are obtained the modification of the criterion and a simple procedure of searching the minimum of the criterion are also discussed the theoretical results derived here are tested by simulation examples

adjoint based airfoil optimization with adaptive isogeometric discontinuous galerkin method abstract in this work an adjoint based airfoil shape optimization algorithm is developed based on the adaptive isogeometric discontinuous galerkin method for compressible euler equations to investigate the significance of each design variable of airfoil b spline parameterization we first parameterize the airfoil by b spline curve approximation with some control points viewed as design variables and build the b spline representation of the flow field with the curve to apply the goal oriented h adaptive isogeometric dg method for flow solution then we compute and employ the discrete adjoint solutions for both multi target error estimation in adaptive mesh refinement with the isogeometric nature not only all the geometrical cells but also the numerical basis functions can be analytically expressed by the design variables indicating that the numerical solutions and objective could be differentiable with respect to those variables consequently the gradient is totally computed in an accurate approach and the sensitivity analysis is thus improved by reducing the spatial discretization error and introducing the analytical expression of derivative to reveal the key parameters for optimization in an intuitive and efficient manner although the sqp optimization algorithm is adopted in the paper the given accurate gradient can be applied to any gradient based optimization algorithm the proposed algorithm is demonstrated on rae2822 airfoil with inviscid transonic flow where the shape is optimized to minimize the drag coefficient at a constrained lift and airfoil area the numerical results show that the drag is much more sensitive to the design variables near the tailing edge at the beginning but sensitivity is reduced when optimal

higher order time integration schemes for aeroelastic applications on unstructured meshes efficient techniques for computational aeroelasticity on unstructured meshes are investigated these include the formulation of a fourth order implicit runge kutta time integration scheme a third order backward difference time integration scheme and a second order backward difference time integration scheme for the coupled system of flow and structural equations strong coupling between the flow solution and structural equations is maintained by fully converging the fully coupled system at each time step or stage the time integration schemes are constructed such that discrete conservation is maintained in the flow solution in the presence of dynamically deforming meshes by verifying the discrete geometric conservation law efficient multigrid solution techniques are devised for solving both the governing flow equations and the mesh motion equations using the same agglomerated coarse levels for both problems the flutter boundary prediction of the agard 445 6 wing is used to demonstrate the accuracy and efficiency of these techniques as well as the sensitivity of flutter boundary prediction to time step size and temporal errors

an accurate moving boundary formulation in cut cell methods a cut cell method for cartesian meshes to simulate viscous compressible flows with moving boundaries is presented we focus on eliminating unphysical oscillations occurring in cartesian grid methods extended to moving boundary problems in these methods cells either lie completely in the fluid or solid region or are intersected by the boundary for the latter cells the time dependent volume fraction lying in the fluid region can be so small that explicit time integration schemes become unstable and a special treatment of these cells is necessary when the boundary moves a fluid cell may become a cut cell or a solid cell may become a small cell at the next time level this causes an abrupt change in the discretization operator and a suddenly modified truncation error of the numerical scheme this temporally discontinuous alteration is shown to act like an unphysical source term which deteriorates the numerical solution i e it generates unphysical oscillations in the hydrodynamic forces exerted on the moving boundary we develop an accurate moving boundary formulation based on the varying discretization operators yielding a cut cell method which avoids these discontinuities results for canonical two and three dimensional test cases evidence the accuracy and robustness of the newly developed scheme

an advancing front delaunay triangulation algorithm designed for robustness abstract a new algorithm is described for generating an unstructured mesh about an arbitrary two dimensional configuration mesh points are generated automatically by the algorithm in a manner which ensures a smooth variation of elements and the resulting triangulation constitutes the delaunay triangulation of these points the algorithm combines the mathematical elegance and efficiency of delaunay triangulation algorithms with the desirable point placement features boundary integrity and robustness that are traditionally associated with advancing front type mesh generation strategies the method offers increased robustness over previous algorithms in that it cannot fail regardless of the initial boundary point distribution and the prescribed cell size distribution throughout the flow field

an implicit explicit eulerian godunov scheme for compressible flow a hybrid implicit explicit scheme is developed for eulerian hydrodynamics the hybridization is a continuous switch and operates on each characteristic field separately the explicit scheme is a version of the second order godunov scheme the implicit method is only first order accurate in time but leads to a block tridiagonal matrix inversion for efficiency and is unconditionally stable for the case of linear advection the methodology is described for the cases of linear advection for nonlinear scalar problems and for gas dynamics an important element of our work is the use of a modified engquist osher flux function in place of the godunov flux several numerical results are presented to demonstrate the properties of the method especially stable numerical shocks at very high cfl numbers and second order accurate steady states

nonlinear black box modeling in system identification a unified overview a nonlinear black box structure for a dynamical system is a model structure that is prepared to describe virtually any nonlinear dynamics there has been considerable recent interest in this area with structures based on neural networks radial basis networks wavelet networks and hinging hyperplanes as well as wavelet transform based methods and models based on fuzzy sets and fuzzy rules this paper describes all these approaches in a common framework from a user s perspective it focuses on what are the common features in the different approaches the choices that have to be made and what considerations are relevant for a successful system identification application of these techniques it is pointed out that the nonlinear structures can be seen as a concatenation of a mapping form observed data to a regression vector and a nonlinear mapping from the regressor space to the output space these mappings are discussed separately the latter mapping is usually formed as a basis function expansion the basis functions are typically formed from one simple scalar function which is modified in terms of scale and location the expansion from the scalar argument to the regressor space is achieved by a radial or a ridge type approach basic techniques for estimating the parameters in the structures are criterion minimization as well as two step procedures where first the relevant basis functions are determined using data and then a linear least squares step to determine the coordinates of the function approximation a particular problem is to deal with the large number of potentially necessary parameters this is handled by making the number of used parameters considerably less than the number of offered parameters by regularization shrinking pruning or regressor selection

identification of wiener systems with binary valued output observations this work is concerned with identification of wiener systems whose outputs are measured by binary valued sensors the system consists of a linear fir finite impulse response subsystem of known order followed by a nonlinear function with a known parametrization structure the parameters of both linear and nonlinear parts are unknown input design identification algorithms and their essential properties are presented under the assumptions that the distribution function of the noise is known and the nonlinearity is continuous and invertible it is shown that under scaled periodic inputs identification of wiener systems can be decomposed into a finite number of core identification problems the concept of joint identifiability of the core problem is introduced to capture the essential conditions under which the wiener system can be identified with binary valued observations under scaled full rank conditions and joint identifiability a strongly convergent algorithm is constructed the algorithm is shown to be asymptotically efficient for the core identification problem hence achieving asymptotic optimality in its convergence rate for computational simplicity recursive algorithms are also developed

kiva 4 the kiva family of codes was developed to simulate the thermal and fluid processes taking place inside an internal combustion engine in this latest version of this open source code kiva 4 the numerics have been generalized to unstructrured meshes this change required modifications to the lagrangian phase of the computations the pressure solution and fundamental changes in the fluxing schemes of the rezoning phase this newest version of the code inherits all the droplet phase capabilities and physical sub models of previous versions the integration of the gas phase equations with moving solid boundaries continues to employ the successful arbitrary lagrangian eulerian ale methodology its new unstructured capability facilitates grid construction in complicated geometries and affords a higher degree of flexibility the numerics of the code emphasizing the new additions are described various computational examples are performed demonstrating the new capabilities of the code