Statistics of reaction progress variable and mixture fraction gradients from DNS of turbulent partially premixed flames

Statistically planar turbulent partially premixed flames for different initial intensities of decaying turbulence have been simulated for global equivalence ratios = 0.7 and 1.0 using three-dimensional, simplified chemistry-based direct numerical simulations (DNS). The simulation parameters are chosen such that the flames represent the thin reaction zones regime combustion. A random bimodal distribution of equivalence ratio is introduced in the unburned gas ahead of the flame to account for the mixture inhomogeneity. The results suggest that the probability density functions (PDFs) of the mixture fraction gradient magnitude |Δξ| (i.e., P(|Δξ|)) can be reasonably approximated using a log-normal distribution. However, this presumed PDF distribution captures only the qualitative nature of the PDF of the reaction progress variable gradient magnitude |Δc| (i.e., P(|Δc|)). It has been found that a bivariate log-normal distribution does not sufficiently capture the quantitative behavior of the joint PDF of |Δξ| and |Δc| (i.e., P(|Δξ|, |Δc|)), and the agreement with the DNS data has been found to be poor in certain regions of the flame brush, particularly toward the burned gas side of the flame brush. Moreover, the variables |Δξ| and |Δc| show appreciable correlation toward the burned gas side of the flame brush. These findings are corroborated further using a DNS data of a lifted jet flame to study the flame geometry dependence of these statistics. © 2013 Copyright Taylor and Francis Group, LLC.

The structure and function of neurons with variable nonlinear transfer function

One novel neuron with variable nonlinear transfer function is firstly proposed, It could also be called as subsection transfer function neuron. With different transfer function components, by virtue of multi-thresholded, the variable transfer function neuron switch on among different nonlinear excitated state. And the comparison of output's transfer characteristics between it and single-thresholded neuron will be illustrated, with some practical application experiments on Bi-level logic operation, at last the simple comparison with conventional BP, RBF, and even DBF NN is taken to expect the development foreground on the variable neuron.. The novel nonlinear transfer function neuron could implement the random nonlinear mapping relationship between input layer and output layer, which could make variable transfer function neuron have one much wider applications on lots of reseach realm such as function approximation pattern recognition data compress and so on.

Modelling random fuzzy renewal reward processes

Shen, Q., Zhao, R., Tang, W. (2008). Modelling random fuzzy renewal reward processes. IEEE Transactions on Fuzzy Systems, 16 (5),1379-1385

Comparison of deterministic, stochastic and fuzzy logic uncertainty modelling for capacity extension projects of DI/WFI pharmaceutical plant utilities with variable/dynamic demand

The last 30 years have seen Fuzzy Logic (FL) emerging as a method either complementing or challenging stochastic methods as the traditional method of modelling uncertainty. But the circumstances under which FL or stochastic methods should be used are shrouded in disagreement, because the areas of application of statistical and FL methods are overlapping with differences in opinion as to when which method should be used. Lacking are practically relevant case studies comparing these two methods. This work compares stochastic and FL methods for the assessment of spare capacity on the example of pharmaceutical high purity water (HPW) utility systems. The goal of this study was to find the most appropriate method modelling uncertainty in industrial scale HPW systems. The results provide evidence which suggests that stochastic methods are superior to the methods of FL in simulating uncertainty in chemical plant utilities including HPW systems in typical cases whereby extreme events, for example peaks in demand, or day-to-day variation rather than average values are of interest. The average production output or other statistical measures may, for instance, be of interest in the assessment of workshops. Furthermore the results indicate that the stochastic model should be used only if found necessary by a deterministic simulation. Consequently, this thesis concludes that either deterministic or stochastic methods should be used to simulate uncertainty in chemical plant utility systems and by extension some process system because extreme events or the modelling of day-to-day variation are important in capacity extension projects. Other reasons supporting the suggestion that stochastic HPW models are preferred to FL HPW models include: 1. The computer code for stochastic models is typically less complex than a FL models, thus reducing code maintenance and validation issues. 2. In many respects FL models are similar to deterministic models. Thus the need for a FL model over a deterministic model is questionable in the case of industrial scale HPW systems as presented here (as well as other similar systems) since the latter requires simpler models. 3. A FL model may be difficult to "sell" to an end-user as its results represent "approximate reasoning" a definition of which is, however, lacking. 4. Stochastic models may be applied with some relatively minor modifications on other systems, whereas FL models may not. For instance, the stochastic HPW system could be used to model municipal drinking water systems, whereas the FL HPW model should or could not be used on such systems. This is because the FL and stochastic model philosophies of a HPW system are fundamentally different. The stochastic model sees schedule and volume uncertainties as random phenomena described by statistical distributions based on either estimated or historical data. The FL model, on the other hand, simulates schedule uncertainties based on estimated operator behaviour e.g. tiredness of the operators and their working schedule. But in a municipal drinking water distribution system the notion of "operator" breaks down. 5. Stochastic methods can account for uncertainties that are difficult to model with FL. The FL HPW system model does not account for dispensed volume uncertainty, as there appears to be no reasonable method to account for it with FL whereas the stochastic model includes volume uncertainty.

Convergence and tracking analysis of a variable normalised LMF (XE-NLMF) algorithm

The least-mean-fourth (LMF) algorithm is known for its fast convergence and lower steady state error, especially in sub-Gaussian noise environments. Recent work on normalised versions of the LMF algorithm has further enhanced its stability and performance in both Gaussian and sub-Gaussian noise environments. For example, the recently developed normalised LMF (XE-NLMF) algorithm is normalised by the mixed signal and error powers, and weighted by a fixed mixed-power parameter. Unfortunately, this algorithm depends on the selection of this mixing parameter. In this work, a time-varying mixed-power parameter technique is introduced to overcome this dependency. A convergence analysis, transient analysis, and steady-state behaviour of the proposed algorithm are derived and verified through simulations. An enhancement in performance is obtained through the use of this technique in two different scenarios. Moreover, the tracking analysis of the proposed algorithm is carried out in the presence of two sources of nonstationarities: (1) carrier frequency offset between transmitter and receiver and (2) random variations in the environment. Close agreement between analysis and simulation results is obtained. The results show that, unlike in the stationary case, the steady-state excess mean-square error is not a monotonically increasing function of the step size. (c) 2007 Elsevier B.V. All rights reserved.

Detailed analytical investigation of magnetic field line random walk in turbulent plasmas: I. Two-component slab/two-dimensional turbulence

The random displacement of magnetic field lines in the presence of magnetic turbulence in plasmas is investigated from first principles. A two-component (slab/two-dimensional composite) model for the turbulence spectrum is employes. An analytical investigation of the asymptotic behavior of the field-line mean square displacement (FL-MSD) is carried out. It is shown that the magnetic field lines behave superdifusively for every large values of the position variable z, since the FL-MSD sigma varies as sigma similar to z(4/3). An intermediate diffusive regime may also possible exist for finite values of z under conditions which are explicitly determined in terms of the intrinsic turbulent plasma parameters. The superdiffusie asymptotic result is confirmed numerically via an iterative algorithm. The relevance to previous resuslts is discussed.

Detailed analytical investigation of magnetic field line random walk in turbulent plasmas: II. Isotropic turbulence

The random walk of magnetic field lines in the presence of magnetic turbulence in plasmas is investigated from first principles. An isotropic model is employed for the magnetic turbulence spectrum. An analytical investigation of the asymptotic behavior of the field-line mean-square displacement is carried out. in terms of the position variable z. It is shown that varies as similar to z ln z for large distance z. This result corresponds to a superdiffusive behavior of field line wandering. This investigation complements previous work, which relied on a two-component model for the turbulence spectrum. Contrary to that model, quasilinear theory appears to provide an adequate description of the field line random walk for isotropic turbulence.

Random particle motion in magnetized plasma

A multivariate Fokker-Planck-type kinetic equation modeling a test - panicle weakly interacting with an electrostatic plasma. in the presence of a magnetic field B . is analytically solved in an Ornstein - Uhlenbeck - type approximation. A new set of analytic expressions are obtained for variable moments and panicle density as a function of time. The process is diffusive.

The C-Terminal Variable Region Specifies the Dynamic Properties of Arabidopsis Microtubule-Associated Protein MAP65 Isotypes

The microtubule-associated protein, MAP65, is a member of a family of divergent microtubule-associated proteins from different organisms generally involved in maintaining the integrity of the central spindle in mitosis. The dicotyledon Arabidopsis thaliana and the monocotyledon rice (Oryza sativa) genomes contain 9 and 11 MAP65 genes, respectively. In this work, we show that the majority of these proteins fall into five phylogenetic clades, with the greatest variation between clades being in the C-terminal random coil domain. At least one Arabidopsis and one rice isotype is within each clade, indicating a functional specification for the C terminus. In At MAP65-1, the C-terminal domain is a microtubule binding region (MTB2) harboring the phosphorylation sites that control its activity. The At MAP65 isotypes show differential localization to microtubule arrays and promote microtubule polymerization with variable efficiency in a MTB2-dependent manner. In vivo studies demonstrate that the dynamics of the association and dissociation of different MAP65 isotypes with microtubules can vary up to 10-fold and that this correlates with their ability to promote microtubule polymerization. Our data demonstrate that the C-terminal variable region, MTB2, determines the dynamic properties of individual isotypes and suggest that slower turnover is conditional for more efficient microtubule polymerization.

Using interviewer random effects to remove selection bias from HIV prevalence estimates

Background: Selection bias in HIV prevalence estimates occurs if non-participation in testing is correlated with HIV status. Longitudinal data suggests that individuals who know or suspect they are HIV positive are less likely to participate in testing in HIV surveys, in which case methods to correct for missing data which are based on imputation and observed characteristics will produce biased results. Methods: The identity of the HIV survey interviewer is typically associated with HIV testing participation, but is unlikely to be correlated with HIV status. Interviewer identity can thus be used as a selection variable allowing estimation of Heckman-type selection models. These models produce asymptotically unbiased HIV prevalence estimates, even when non-participation is correlated with unobserved characteristics, such as knowledge of HIV status. We introduce a new random effects method to these selection models which overcomes non-convergence caused by collinearity, small sample bias, and incorrect inference in existing approaches. Our method is easy to implement in standard statistical software, and allows the construction of bootstrapped standard errors which adjust for the fact that the relationship between testing and HIV status is uncertain and needs to be estimated. Results: Using nationally representative data from the Demographic and Health Surveys, we illustrate our approach with new point estimates and confidence intervals (CI) for HIV prevalence among men in Ghana (2003) and Zambia (2007). In Ghana, we find little evidence of selection bias as our selection model gives an HIV prevalence estimate of 1.4% (95% CI 1.2% – 1.6%), compared to 1.6% among those with a valid HIV test. In Zambia, our selection model gives an HIV prevalence estimate of 16.3% (95% CI 11.0% - 18.4%), compared to 12.1% among those with a valid HIV test. Therefore, those who decline to test in Zambia are found to be more likely to be HIV positive. Conclusions: Our approach corrects for selection bias in HIV prevalence estimates, is possible to implement even when HIV prevalence or non-participation is very high or very low, and provides a practical solution to account for both sampling and parameter uncertainty in the estimation of confidence intervals. The wide confidence intervals estimated in an example with high HIV prevalence indicate that it is difficult to correct statistically for the bias that may occur when a large proportion of people refuse to test.

Variable Window Power Spectral Density Attack

Side channel attacks permit the recovery of the secret key held within a cryptographic device. This paper presents a new EM attack in the frequency domain, using a power spectral density analysis that permits the use of variable spectral window widths for each trace of the data set and demonstrates how this attack can therefore overcome both inter-and intra-round random insertion type countermeasures. We also propose a novel re-alignment method exploiting the minimal power markers exhibited by electromagnetic emanations. The technique can be used for the extraction and re-alignment of round data in the time domain.

New stimuli-responsive block random copolymers and their aggregation

Les polymères sensibles à des stimuli ont été largement étudiés ces dernières années notamment en vue d’applications biomédicales. Ceux-ci ont la capacité de changer leurs propriétés de solubilité face à des variations de pH ou de température. Le but de cette thèse concerne la synthèse et l’étude de nouveaux diblocs composés de deux copolymères aléatoires. Les polymères ont été obtenus par polymérisation radicalaire contrôlée du type RAFT (reversible addition-fragmentation chain-transfer). Les polymères à bloc sont formés de monomères de méthacrylates et/ou d’acrylamides dont les polymères sont reconnus comme thermosensibles et sensible au pH. Premièrement, les copolymères à bloc aléatoires du type AnBm-b-ApBq ont été synthétisés à partir de N-n-propylacrylamide (nPA) et de N-ethylacrylamide (EA), respectivement A et B, par polymérisation RAFT. La cinétique de copolymérisation des poly(nPAx-co-EA1-x)-block-poly(nPAy-co-EA1-y) et leur composition ont été étudiées afin de caractériser et évaluer les propriétés physico-chimiques des copolymères à bloc aléatoires avec un faible indice de polydispersité . Leurs caractères thermosensibles ont été étudiés en solution aqueuse par spectroscopie UV-Vis, turbidimétrie et analyse de la diffusion dynamique de la lumière (DLS). Les points de trouble (CP) observés des blocs individuels et des copolymères formés démontrent des phases de transitions bien définies lors de la chauffe. Un grand nombre de macromolécules naturels démontrent des réponses aux stimuli externes tels que le pH et la température. Aussi, un troisième monomère, 2-diethylaminoethyl methacrylate (DEAEMA), a été ajouté à la synthèse pour former des copolymères à bloc , sous la forme AnBm-b-ApCq , et qui offre une double réponse (pH et température), modulable en solution. Ce type de polymère, aux multiples stimuli, de la forme poly(nPAx-co-DEAEMA1-x)-block-poly(nPAy-co-EA1-y), a lui aussi été synthétisé par polymérisation RAFT. Les résultats indiquent des copolymères à bloc aléatoires aux propriétés physico-chimiques différentes des premiers diblocs, notamment leur solubilité face aux variations de pH et de température. Enfin, le changement d’hydrophobie des copolymères a été étudié en faisant varier la longueur des séquences des blocs. Il est reconnu que la longueur relative des blocs affecte les mécanismes d’agrégation d’un copolymère amphiphile. Ainsi avec différents stimuli de pH et/ou de température, les expériences effectuées sur des copolymères à blocaléatoires de différentes longueurs montrent des comportements d’agrégation intéressants, évoluant sous différentes formes micellaires, d’agrégats et de vésicules.

Coordinating Inventory Control and Pricing Strategies with Random Demand and Fixed Ordering Cost: The Finite Horizon Case

We analyze a finite horizon, single product, periodic review model in which pricing and production/inventory decisions are made simultaneously. Demands in different periods are random variables that are independent of each other and their distributions depend on the product price. Pricing and ordering decisions are made at the beginning of each period and all shortages are backlogged. Ordering cost includes both a fixed cost and a variable cost proportional to the amount ordered. The objective is to find an inventory policy and a pricing strategy maximizing expected profit over the finite horizon. We show that when the demand model is additive, the profit-to-go functions are k-concave and hence an (s,S,p) policy is optimal. In such a policy, the period inventory is managed based on the classical (s,S) policy and price is determined based on the inventory position at the beginning of each period. For more general demand functions, i.e., multiplicative plus additive functions, we demonstrate that the profit-to-go function is not necessarily k-concave and an (s,S,p) policy is not necessarily optimal. We introduce a new concept, the symmetric k-concave functions and apply it to provide a characterization of the optimal policy.

Coordinating Inventory Control and Pricing Strategies with Random Demand and Fixed Ordering Cost: the Infinite Horizon Case

We analyze an infinite horizon, single product, periodic review model in which pricing and production/inventory decisions are made simultaneously. Demands in different periods are identically distributed random variables that are independent of each other and their distributions depend on the product price. Pricing and ordering decisions are made at the beginning of each period and all shortages are backlogged. Ordering cost includes both a fixed cost and a variable cost proportional to the amount ordered. The objective is to maximize expected discounted, or expected average profit over the infinite planning horizon. We show that a stationary (s,S,p) policy is optimal for both the discounted and average profit models with general demand functions. In such a policy, the period inventory is managed based on the classical (s,S) policy and price is determined based on the inventory position at the beginning of each period.

Synapsing variable length crossover: An algorithm for crossing and comparing variable length genomes

The Synapsing Variable Length Crossover (SVLC) algorithm provides a biologically inspired method for performing meaningful crossover between variable length genomes. In addition to providing a rationale for variable length crossover it also provides a genotypic similarity metric for variable length genomes enabling standard niche formation techniques to be used with variable length genomes. Unlike other variable length crossover techniques which consider genomes to be rigid inflexible arrays and where some or all of the crossover points are randomly selected, the SVLC algorithm considers genomes to be flexible and chooses non-random crossover points based on the common parental sequence similarity. The SVLC Algorithm recurrently "glues" or synapses homogenous genetic sub-sequences together. This is done in such a way that common parental sequences are automatically preserved in the offspring with only the genetic differences being exchanged or removed, independent of the length of such differences. In a variable length test problem the SVLC algorithm is shown to outperform current variable length crossover techniques. The SVLC algorithm is also shown to work in a more realistic robot neural network controller evolution application.