A backward-simulation based Rao-Blackwellized particle smoother for conditionally linear Gaussian models

In this article, we develop a new Rao-Blackwellized Monte Carlo smoothing algorithm for conditionally linear Gaussian models. The algorithm is based on the forward-filtering backward-simulation Monte Carlo smoother concept and performs the backward simulation directly in the marginal space of the non-Gaussian state component while treating the linear part analytically. Unlike the previously proposed backward-simulation based Rao-Blackwellized smoothing approaches, it does not require sampling of the Gaussian state component and is also able to overcome certain normalization problems of two-filter smoother based approaches. The performance of the algorithm is illustrated in a simulated application. © 2012 IFAC.

Rao-Blackwellized particle smoothers for mixed linear/nonlinear state-space models

We consider the smoothing problem for a class of conditionally linear Gaussian state-space (CLGSS) models, referred to as mixed linear/nonlinear models. In contrast to the better studied hierarchical CLGSS models, these allow for an intricate cross dependence between the linear and the nonlinear parts of the state vector. We derive a Rao-Blackwellized particle smoother (RBPS) for this model class by exploiting its tractable substructure. The smoother is of the forward filtering/backward simulation type. A key feature of the proposed method is that, unlike existing RBPS for this model class, the linear part of the state vector is marginalized out in both the forward direction and in the backward direction. © 2013 IEEE.

一种改进的数据求精证明规则

提出一种改进的数据求精规则，并用关系模式进行描述。引入全局状态来描述程序所有可能的输入和输出，允许非平凡的初始化，允许前向模拟和后向模拟，能应用于消除具体模型的不确定性晚于消除抽象模型的不确定性的情况。并用实例说明了在Isabelle定理证明器中规则的应用方法。

Large-eddy simulation of heat transfer downstream of a backward-facing step

Large-eddy simulation is used to predict heat transfer in the separated and reattached flow regions downstream of a backward-facing step. Simulations were carried out at a Reynolds number of 28 000 (based on the step height and the upstream centreline velocity) with a channel expansion ratio of 1.25. The Prandtl number was 0.71. Two subgrid-scale models were tested, namely the dynamic eddy-viscosity, eddy-diffusivity model and the dynamic mixed model. Both models showed good overall agreement with available experimental data. The simulations indicated that the peak in heat-transfer coefficient occurs slightly upstream of the mean reattachment location, in agreement with experimental data. The results of these simulations have been analysed to discover the mechanisms that cause this phenomenon. The peak in heat-transfer coefficient shows a direct correlation with the peak in wall shear-stress fluctuations. It is conjectured that the peak in these fluctuations is caused by an impingement mechanism, in which large eddies, originating in the shear layer, impact the wall just upstream of the mean reattachment location. These eddies cause a 'downwash', which increases the local heat-transfer coefficient by bringing cold fluid from above the shear layer towards the wall.

Efficient simulation of unsaturated flow using exponential time integration

We assess the performance of an exponential integrator for advancing stiff, semidiscrete formulations of the unsaturated Richards equation in time. The scheme is of second order and explicit in nature but requires the action of the matrix function φ(A) where φ(z) = [exp(z) - 1]/z on a suitability defined vector v at each time step. When the matrix A is large and sparse, φ(A)v can be approximated by Krylov subspace methods that require only matrix-vector products with A. We prove that despite the use of this approximation the scheme remains second order. Furthermore, we provide a practical variable-stepsize implementation of the integrator by deriving an estimate of the local error that requires only a single additional function evaluation. Numerical experiments performed on two-dimensional test problems demonstrate that this implementation outperforms second-order, variable-stepsize implementations of the backward differentiation formulae.

An efficient forward-backward algorithm to MSDEPP including batteries and voltage control devices

Electric distribution networks are now in the era of transition from passive to active distribution networks with the integration of energy storage devices. Optimal usage of batteries and voltage control devices along with other upgrades in network needs a distribution expansion planning (DEP) considering inter-temporal dependencies of stages. This paper presents an efficient approach for solving multi-stage distribution expansion planning problems (MSDEPP) based on a forward-backward approach considering energy storage devices such as batteries and voltage control devices such as voltage regulators and capacitors. The proposed algorithm is compared with three other techniques including full dynamic, forward fill-in, backward pull-out from the point of view of their precision and their computational efficiency. The simulation results for the IEEE 13 bus network show the proposed pseudo-dynamic forward-backward approach presents good efficiency in precision and time of optimization.

Efficient simulation of unsaturated flow in heterogeneous soils using an exponential integrator

- Provided a practical variable-stepsize implementation of the exponential Euler method (EEM). - Introduced a new second-order variant of the scheme that enables the local error to be estimated at the cost of a single additional function evaluation. - New EEM implementation outperformed sophisticated implementations of the backward differentiation formulae (BDF) of order 2 and was competitive with BDF of order 5 for moderate to high tolerances.

Statistical user simulation with a hidden agenda

Recent work in the area of probabilistic user simulation for training statistical dialogue managers has investigated a new agenda-based user model and presented preliminary experiments with a handcrafted model parameter set. Training the model on dialogue data is an important next step, but non-trivial since the user agenda states are not observable in data and the space of possible states and state transitions is intractably large. This paper presents a summary-space mapping which greatly reduces the number of state transitions and introduces a tree-based method for representing the space of possible agenda state sequences. Treating the user agenda as a hidden variable, the forward/backward algorithm can then be successfully applied to iteratively estimate the model parameters on dialogue data. © 2007 Association for Computational Linguistics.

GSHMC: an efficient method for molecular simulation

The hybrid Monte Carlo (HMC) method is a popular and rigorous method for sampling from a canonical ensemble. The HMC method is based on classical molecular dynamics simulations combined with a Metropolis acceptance criterion and a momentum resampling step. While the HMC method completely resamples the momentum after each Monte Carlo step, the generalized hybrid Monte Carlo (GHMC) method can be implemented with a partial momentum refreshment step. This property seems desirable for keeping some of the dynamic information throughout the sampling process similar to stochastic Langevin and Brownian dynamics simulations. It is, however, ultimate to the success of the GHMC method that the rejection rate in the molecular dynamics part is kept at a minimum. Otherwise an undesirable Zitterbewegung in the Monte Carlo samples is observed. In this paper, we describe a method to achieve very low rejection rates by using a modified energy, which is preserved to high-order along molecular dynamics trajectories. The modified energy is based on backward error results for symplectic time-stepping methods. The proposed generalized shadow hybrid Monte Carlo (GSHMC) method is applicable to NVT as well as NPT ensemble simulations.

Backward modelling and look-ahead fuzzy energy management controller for a parallel hybrid vehicle

This paper focuses on a parallel hybrid electric vehicle. It first develops a model for the vehicle using the backward-looking approach where the flow of energy starts from wheels and spreads towards engine and electric motor. Next, a fuzzy logic-based strategy is developed to control the operation of the vehicle. The objectives of the controller include managing the energy flow from engine and electric motor, controlling transmission ratio, adjusting speed, and sustaining battery's state of charge. The controller examines current vehicle speed, demand torque, slope difference, state of charge of battery, and engine and electric motor rotation speeds. Then, it determines the best values for continuous variable transmission ratio, speed, and torque. A slope window scheme is also developed to take into account the look-ahead slope information and determine the best vehicle speed for better fuel economy. The developed model and control strategy are simulated. The simulation results are presented and discussed. It is shown that the use of the proposed fuzzy controller reduces fuel consumption.

A non-associated plasticity model with anisotropic and nonlinear kinematic hardening for simulation of sheet metal forming

A material model for more thorough analysis of plastic deformation of sheet materials is presented in this paper. This model considers the following aspects of plastic deformation behavior of sheet materials: (1) the anisotropy in yield stresses and in work hardening by using Hill's 1948 quadratic yield function and non-constant stress ratios which leads to different flow stress hardening in different directions, (2) the anisotropy in plastic strains by using a quadratic plastic potential function and non-associated flow rule, also based on Hill's 1948 model and r-values, and (3) the cyclic hardening phenomena such as the Bauschinger effect, permanent softening and transient behavior for reverse loading by using a coupled nonlinear kinematic hardening model. Plasticity fundamentals of the model were derived in a general framework and the model calibration procedure was presented for the plasticity formulations. Also, a generic numerical stress integration procedure was developed based on backward-Euler method, so-called multi-stage return mapping algorithm. The model was implemented in the framework of the finite element method to evaluate the simulation results of sheet metal forming processes. Different aspects of the model were verified for two sheet metals, namely DP600 steel and AA6022 aluminum alloy. Results show that the new model is able to accurately predict the sheet material behavior for both anisotropic hardening and cyclic hardening conditions. The drawing of channel sections and the subsequent springback were also simulated with this model for different drawbead configurations. Simulation results show that the current non-associated anisotropic hardening model is able to accurately predict the sidewall curl in the drawn channel sections.

Measurement of the forward-backward asymmetry of Z boson decays in electron-positron pairs with the ATLAS detector in proton-proton collisions at root out s = 7TeV at the LHC

In this thesis the measurement of the effective weak mixing angle wma in proton-proton collisions is described. The results are extracted from the forward-backward asymmetry (AFB) in electron-positron final states at the ATLAS experiment at the LHC. The AFB is defined upon the distribution of the polar angle between the incoming quark and outgoing lepton. The signal process used in this study is the reaction pp to zgamma + X to ee + X taking a total integrated luminosity of 4.8\,fb^(-1) of data into account. The data was recorded at a proton-proton center-of-mass energy of sqrt(s)=7TeV. The weak mixing angle is a central parameter of the electroweak theory of the Standard Model (SM) and relates the neutral current interactions of electromagnetism and weak force. The higher order corrections on wma are related to other SM parameters like the mass of the Higgs boson.rnrnBecause of the symmetric initial state constellation of colliding protons, there is no favoured forward or backward direction in the experimental setup. The reference axis used in the definition of the polar angle is therefore chosen with respect to the longitudinal boost of the electron-positron final state. This leads to events with low absolute rapidity have a higher chance of being assigned to the opposite direction of the reference axis. This effect called dilution is reduced when events at higher rapidities are used. It can be studied including electrons and positrons in the forward regions of the ATLAS calorimeters. Electrons and positrons are further referred to as electrons. To include the electrons from the forward region, the energy calibration for the forward calorimeters had to be redone. This calibration is performed by inter-calibrating the forward electron energy scale using pairs of a central and a forward electron and the previously derived central electron energy calibration. The uncertainty is shown to be dominated by the systematic variations.rnrnThe extraction of wma is performed using chi^2 tests, comparing the measured distribution of AFB in data to a set of template distributions with varied values of wma. The templates are built in a forward folding technique using modified generator level samples and the official fully simulated signal sample with full detector simulation and particle reconstruction and identification. The analysis is performed in two different channels: pairs of central electrons or one central and one forward electron. The results of the two channels are in good agreement and are the first measurements of wma at the Z resonance using electron final states at proton-proton collisions at sqrt(s)=7TeV. The precision of the measurement is already systematically limited mostly by the uncertainties resulting from the knowledge of the parton distribution functions (PDF) and the systematic uncertainties of the energy calibration.rnrnThe extracted results of wma are combined and yield a value of wma_comb = 0.2288 +- 0.0004 (stat.) +- 0.0009 (syst.) = 0.2288 +- 0.0010 (tot.). The measurements are compared to the results of previous measurements at the Z boson resonance. The deviation with respect to the combined result provided by the LEP and SLC experiments is up to 2.7 standard deviations.

A biophysical model of synaptic plasticity and metaplasticity can account for the dynamics of the backward shift of hippocampal place fields.

Hippocampal place cells in the rat undergo experience-dependent changes when the rat runs stereotyped routes. One such change, the backward shift of the place field center of mass, has been linked by previous modeling efforts to spike-timing-dependent plasticity (STDP). However, these models did not account for the termination of the place field shift and they were based on an abstract implementation of STDP that ignores many of the features found in cortical plasticity. Here, instead of the abstract STDP model, we use a calcium-dependent plasticity (CaDP) learning rule that can account for many of the observed properties of cortical plasticity. We use the CaDP learning rule in combination with a model of metaplasticity to simulate place field dynamics. Without any major changes to the parameters of the original model, the present simulations account both for the initial rapid place field shift and for the subsequent slowing down of this shift. These results suggest that the CaDP model captures the essence of a general cortical mechanism of synaptic plasticity, which may underlie numerous forms of synaptic plasticity observed both in vivo and in vitro.