The Gaussian process density sampler

We present the Gaussian Process Density Sampler (GPDS), an exchangeable generative model for use in nonparametric Bayesian density estimation. Samples drawn from the GPDS are consistent with exact, independent samples from a fixed density function that is a transformation of a function drawn from a Gaussian process prior. Our formulation allows us to infer an unknown density from data using Markov chain Monte Carlo, which gives samples from the posterior distribution over density functions and from the predictive distribution on data space. We can also infer the hyperparameters of the Gaussian process. We compare this density modeling technique to several existing techniques on a toy problem and a skullreconstruction task.

Closing the gap: Improved bounds on optimal POMDP solutions

POMDP algorithms have made significant progress in recent years by allowing practitioners to find good solutions to increasingly large problems. Most approaches (including point-based and policy iteration techniques) operate by refining a lower bound of the optimal value function. Several approaches (e.g., HSVI2, SARSOP, grid-based approaches and online forward search) also refine an upper bound. However, approximating the optimal value function by an upper bound is computationally expensive and therefore tightness is often sacrificed to improve efficiency (e.g., sawtooth approximation). In this paper, we describe a new approach to efficiently compute tighter bounds by i) conducting a prioritized breadth first search over the reachable beliefs, ii) propagating upper bound improvements with an augmented POMDP and iii) using exact linear programming (instead of the sawtooth approximation) for upper bound interpolation. As a result, we can represent the bounds more compactly and significantly reduce the gap between upper and lower bounds on several benchmark problems. Copyright © 2011, Association for the Advancement of Artificial Intelligence. All rights reserved.

The statistics of the second order response of an FPSO in spreading seas

An expression for the probability density function of the second order response of a general FPSO in spreading seas is derived by using the Kac-Siegert approach. Various approximations of the second order force transfer functions are investigated for a ship-shaped FPSO. It is found that, when expressed in non-dimensional form, the probability density function of the response is not particularly sensitive to wave spreading, although the mean squared response and the resulting dimensional extreme values can be sensitive. The analysis is then applied to a Sevan FPSO, which is a large cylindrical buoy-like structure. The second order force transfer functions are derived by using an efficient semi-analytical hydrodynamic approach, and these are then employed to yield the extreme response. However, a significant effect of wave spreading on the statistics for a Sevan FPSO is found even in non-dimensional form. It implies that the exact statistics of a general ship-shaped FPSO may be sensitive to the wave direction, which needs to be verified in future work. It is also pointed out that the Newman's approximation regarding the frequency dependency of force transfer function is acceptable even for the spreading seas. An improvement on the results may be attained when considering the angular dependency exactly. Copyright © 2009 by ASME.

Bayesian learning of noisy Markov decision processes

This work addresses the problem of estimating the optimal value function in a Markov Decision Process from observed state-action pairs. We adopt a Bayesian approach to inference, which allows both the model to be estimated and predictions about actions to be made in a unified framework, providing a principled approach to mimicry of a controller on the basis of observed data. A new Markov chain Monte Carlo (MCMC) sampler is devised for simulation from theposterior distribution over the optimal value function. This step includes a parameter expansion step, which is shown to be essential for good convergence properties of the MCMC sampler. As an illustration, the method is applied to learning a human controller.

Designing MPC controllers by reverse-engineering existing LTI controllers

This technical report presents a method for designing a constrained output-feedback model predictive controller (MPC) that behaves in the same way as an existing baseline stabilising linear time invariant output-feedback controller when constraints are inactive. The baseline controller is cast into an observer-compensator form and an inverse-optimal cost function is used as the basis of the MPC controller. The available degrees of design freedom are explored, and some guidelines provided for the selection of an appropriate observer-compensator realisation that will best allow exploitation of the constraint-handling and redundancy management capabilities of MPC. Consideration is given to output setpoint tracking, and the method is demonstrated with three different multivariable plants of varying complexity.

Three-dimensional direct numerical simulations of autoignition in turbulent non-premixed flows with simple and complex chemistry

3D Direct Numerical Simulations (DNS) of autoignition in turbulent non-premixed flows between fuel and hotter air have been carried out using both 1-step and complex chemistry consisting of a 22 species n-heptane mechanism to investigate spontaneous ignition timing and location. The simple chemistry results showed that the previous findings from 2D DNS that ignition occurred at the most reactive mixture fraction (ξMR) and at small values of the conditional scalar dissipation rate (N|ξMR) are valid also for 3D turbulent mixing fields. Performing the same simulation many times with different realizations of the initial velocity field resulted in a very narrow statistical distribution of ignition delay time, consistent with a previous conjecture that the first appearance of ignition is correlated with the low-N content of the conditional probability density function of N. The simulations with complex chemistry for conditions outside the Negative Temperature Coefficient (NTC) regime show behaviour similar to the single-step chemistry simulations. However, in the NTC regime, the most reactive mixture fraction is very rich and ignition seems to occur at high values of scalar dissipation. Copyright © 2006 by ASME.

Effects of turbulent reynolds number on the displacement speed statistics in the thin reaction zones regime of turbulent premixed combustion

The effects of turbulent Reynolds number on the statistical behaviour of the displacement speed have been studied using three-dimensional Direct Numerical Simulation of statistically planar turbulent premixed flames. The probability of finding negative values of the displacement speed is found to increase with increasing turbulent Reynolds number when the Damkhler number is held constant. It has been shown that the statistical behaviour of the Surface Density Function, and its strain rate and curvature dependence, plays a key role in determining the response of the different components of displacement speed. Increasing the turbulent Reynolds number is shown to reduce the strength of the correlations between tangential strain rate and dilatation rate with curvature, although the qualitative nature of the correlations remains unaffected. The dependence of displacement speed on strain rate and curvature is found to weaken with increasing turbulent Reynolds number when either Damkhler or Karlovitz number is held constant, but the qualitative nature of the correlation remains unaltered. The implications of turbulent Reynolds number effects in the context of Flame Surface Density (FSD) modelling have also been addressed, with emphasis on the influence of displacement speed on the curvature and propagation terms in the FSD balance equation. © 2011 Nilanjan Chakraborty et al.

Verifying stability of approximate explicit MPC

Several authors have proposed algorithms for approximate explicit MPC [1],[2],[3]. These algorithms have in common that they develop a stability criterion for approximate explicit MPC that require the approximate cost function to be within a certain distance from the optimal cost function. In this paper, stability is instead ascertained by considering only the cost function of the approximate MPC. If a region of the state space is found where the cost function is not decreasing, this indicates that an improved approximation (to the optimal control) is required in that region. If the approximate cost function is decreasing everywhere, no further refinement of the approximate MPC is necessary, since stability is guaranteed. ©2009 IEEE.

Response probability distribution of built-up vibro-acoustic systems

The vibro-acoustic response of built-up structures, consisting of stiff components with low modal density and flexible components with high modal density, is sensitive to small imperfections in the flexible components. In this paper, the uncertainty of the response is considered by modeling the low modal density master system as deterministic and the high modal density subsystems in a nonparametric stochastic way, i.e., carrying a diffuse wave field, and by subsequently computing the response probability density function. The master system's mean squared response amplitude follows a singular noncentral complex Wishart distribution conditional on the subsystem energies. For a single degree of freedom, this is equivalent to a chi-square or an exponential distribution, depending on the loading conditions. The subsystem energies follow approximately a chi-square distribution when their relative variance is smaller than unity. The results are validated by application to plate structures, and good agreement with Monte Carlo simulations is found. © 2012 Acoustical Society of America.

The structure of turbulent stratified and premixed methane/air flames I: Non-swirling flows

A series of flames in a turbulent methane/air stratified swirl burner is presented. The degree of stratification and swirl are systematically varied to generate a matrix of experimental conditions, allowing their separate and combined effects to be investigated. Non-swirling flows are considered in the present paper, and the effects of swirl are considered in a companion paper (Part II). A mean equivalence ratio of φ=0.75 is used, with φ for the highest level of stratification spanning 0.375-1.125. The burner features a central bluff-body to aid flame stabilization, and the influence of the induced recirculation zone is also considered. The current work focuses on non-swirling flows where two-component particle image velocimetry (PIV) measurements are sufficient to characterize the main features of the flow field. Scalar data obtained from Rayleigh/Raman/CO laser induced fluorescence (CO-LIF) line measurements at 103μm resolution allow the behavior of key combustion species-CH 4, CO 2, CO, H 2, H 2O and O 2-to be probed within the instantaneous flame front. Simultaneous cross-planar OH-PLIF is used to determine the orientation of the instantaneous flame normal in the scalar measurement window, allowing gradients in temperature and progress variable to be angle corrected to their three dimensional values. The relationship between curvature and flame thickness is investigated using the OH-PLIF images, as well as the effect of stratification on curvature.The main findings are that the behavior of the key combustion species in temperature space is well captured on the mean by laminar flame calculations regardless of the level of stratification. H 2 and CO are significant exceptions, both appearing at elevated levels in the stratified flames. Values for surface density function and by extension thermal scalar dissipation rate are found to be substantially lower than laminar values, as the thickening of the flame due to turbulence dominates the effect of increased strain. These findings hold for both premixed and stratified flames. The current series of flames is proposed as an interesting if challenging set of test cases for existing and emerging turbulent flame models, and data are available on request. © 2012 The Combustion Institute.