Delayed control of a Moore-Greitzer axial compressor model

Several feedback control laws have appeared in the literature concerning the stabilization of the nonlinear Moore-Greitzer axial compression model. Motivated by magnitude and rate limitations imposed by the physical implementation of the control law, Larsen et al. studied a dynamic implementation of the S-controller suggested by Sepulchre and Kokotović. They showed the potential benefit of implementing the S-controller through a first-order lag: while the location of the closed-loop equilibrium achieved with the static control law was sensitive to poorly known parameters, the dynamic implementation resulted in a small limit cycle at a very desirable location, insensitive to parameter variations. In this paper, we investigate the more general case when the control is applied with a time delay. This can be seen as an extension of the model with a first-order lag. The delay can either be a result of system constraints or be deliberately implemented to achieve better system behavior. The resulting closed-loop system is a set of parameter-dependent delay differential equations. Numerical bifurcation analysis is used to study this model and investigate whether the positive results obtained for the first-order model persist, even for larger values of the delay.

Application of scalar dissipation rate model to siemens DLE combustors

The standard design process for the Siemens Industrial Turbomachinery, Lincoln, Dry Low Emissions combustion systems has adopted the Eddy Dissipation Model with Finite Rate Chemistry for reacting computational fluid dynamics simulations. The major drawbacks of this model have been the over-prediction of temperature and lack of species data limiting the applicability of the model. A novel combustion model referred to as the Scalar Dissipation Rate Model has been developed recently based on a flamelet type assumption. Previous attempts to adopt the flamelet philosophy with alternative closure models have failed, with the prediction of unphysical phenomenon. The Scalar Dissipation Rate Model (SDRM) was developed from a physical understanding of scalar dissipation rate, signifying the rate of mixing of hot and cold fluids at scales relevant to sustain combustion, in flames and was validated using direct numerical simulations data and experimental measurements. This paper reports on the first industrial application of the SDRM to SITL DLE combustion system. Previous applications have considered ideally premixed laboratory scale flames. The industrial application differs significantly in the complexity of the geometry, unmixedness and operating pressures. The model was implemented into ANSYS-CFX using their inbuilt command language. Simulations were run transiently using Scale Adaptive Simulation turbulence model, which switches between Large Eddy Simulation and Unsteady Reynolds Averaged Navier Stokes using a blending function. The model was validated in a research SITL DLE combustion system prior to being applied to the actual industrial geometry at real operating conditions. This system consists of the SGT-100 burner with a glass square-sectioned combustor allowing for detailed diagnostics. This paper shows the successful validation of the SDRM against time averaged temperature and velocity within measurement errors. The successful validation allowed application of the SDRM to the SGT-100 twin shaft at the relevant full load conditions. Limited validation data was available due to the complexity of measurement in the real geometry. Comparison of surface temperatures and combustor exit temperature profiles showed an improvement compared to EDM/FRC model. Furthermore, no unphysical phenomena were predicted. This paper presents the successful application of the SDRM to the industrial combustion system. The model shows a marked improvement in the prediction of temperature over the EDM/FRC model previously used. This is of significant importance in the future applications of combustion CFD for understanding of hardware mechanical integrity, combustion emissions and dynamics of the flame. Copyright © 2012 by ASME.

Training and assignment of multi-skilled workers for implementing seru production systems

Confronted with high variety and low volume market demands, many companies, especially the Japanese electronics manufacturing companies, have reconfigured their conveyor assembly lines and adopted seru production systems. Seru production system is a new type of work-cell-based manufacturing system. A lot of successful practices and experience show that seru production system can gain considerable flexibility of job shop and high efficiency of conveyor assembly line. In implementing seru production, the multi-skilled worker is the most important precondition, and some issues about multi-skilled workers are central and foremost. In this paper, we investigate the training and assignment problem of workers when a conveyor assembly line is entirely reconfigured into several serus. We formulate a mathematical model with double objectives which aim to minimize the total training cost and to balance the total processing times among multi-skilled workers in each seru. To obtain the satisfied task-to-worker training plan and worker-to-seru assignment plan, a three-stage heuristic algorithm with nine steps is developed to solve this mathematical model. Then, several computational cases are taken and computed by MATLAB programming. The computation and analysis results validate the performances of the proposed mathematical model and heuristic algorithm. © 2013 Springer-Verlag London.

Efficient decoding with generative score-spaces using the expectation semiring

State-of-the-art speech recognisers are usually based on hidden Markov models (HMMs). They model a hidden symbol sequence with a Markov process, with the observations independent given that sequence. These assumptions yield efficient algorithms, but limit the power of the model. An alternative model that allows a wide range of features, including word- and phone-level features, is a log-linear model. To handle, for example, word-level variable-length features, the original feature vectors must be segmented into words. Thus, decoding must find the optimal combination of segmentation of the utterance into words and word sequence. Features must therefore be extracted for each possible segment of audio. For many types of features, this becomes slow. In this paper, long-span features are derived from the likelihoods of word HMMs. Derivatives of the log-likelihoods, which break the Markov assumption, are appended. Previously, decoding with this model took cubic time in the length of the sequence, and longer for higher-order derivatives. This paper shows how to decode in quadratic time. © 2013 IEEE.

Modular hybrid dilated Mach-Zehnder switch with integrated SOAs for large port count switches

A modular dilated MZI based optical switch with integrated SOAs is demonstrated with excellent -40dB crosstalk/extinction ratio, 3ns switching time and nearly penalty-free operation. Studies show an 8×8 switch with 14dB IPDR for 0.5dB penalty. © 2014 OSA.