A model of the interaction of pressure changes with strained premixed flames is formulated by extending previous work on interactions with nonstrained flames. By making the assumption of no divergence in the velocity field (∇ · u = 0) and writing the full equations in terms of mass-weighted coordinates (with explicit strain terms) following the flame sheet, we study the time-varying response of the mass burning rate to an imposed pressure disturbance. Numerical solution of the full nonlinear equations shows that strain has a strong effect on the flame response. It is found that, for large amplitude step pressure drops, the flame does not recover for moderate and small strain rates. As expected, for larger positive strain rates the flame recovers, because it is known that positive strain stabilizes premixed flames. The reverse happens for flames experiencing pressure drops in a convergent flow (negative strain). In this case, extinction of the flame by pressure drops becomes more likely as the convergence of the flow increases. Of particular interest for the negative strain case is the onset of the pulsating instability for a finite range of small values of pressure drop, which then gives way to a region of recovery if the pressure drop is larger, before finally for larger drops the extinction pressure drop is reached.
Gravitational and other anomalies seen repeatedly in connection with solar eclipses have led to speculation about a possible gravitational shielding effect as the cause. Here we show that an unusual phenomenon that occurs only during solar eclipses, rapid air mass movement for the bulk of the atmosphere above normal cloud levels, appears to be a sufficient explanation for both the magnitude and behavior of the anomaly previously reported in these pages.
Computational optimization forms an integrated part of modern computational science. Any good design should intend to achieve certain optimality, though optimal solutions are often difficult to find in practice since uncertainty and nonlinearity always present in almost all real-world problems. As resources, time and money are always limited, optimization becomes even more important in practice. This workshop on Computational Optimization, Modelling and Simulation (COMS 2010) at ICCS 2010 will summarize the latest developments of optimization and modelling and their applications in science, engineering and industry
The use of frequency-derivation information incorporated with model-based parameter estimation (MBPE) to predict the scattering from conducting and dielectric two-dimensional tragets over a frequency band is summarised. Instead of computing a method of moment solution using a point-by-point approach, a rational function model is used to approximate the current as a function of frequency. The model coefficients are computed using frequency-derivative information at one frequency within the band to improve efficiency of conventional moment method approaches. Results show that the model based approach gives excellent results over a limited frequency band, and is much more efficient than the converntional point-by-point approach.
Bacterial transport in saturated–unsaturated soils is an important process in environmental science and hydrology. A mechanistic model for bacterial transport in geomaterials is presented here. The model equations comprise a pair of fully coupled non‐linear parabolic partial differential equations that describe the concentration of microbes in the liquid water and solid surfaces. The model equations not only describe the bacteria sorption and desorption processes, but also take into account the retention of bacteria at the liquid–water interface and the dynamic reproduction characteristics of the bacteria. The instability and travelling waves for the coupled equations are analysed. Copyright © 2004 John Wiley & Sons, Ltd.
A mathematical model is presented for pressure interactions with premixed flames in a prescribed strained velocity field. A stability analysis is carried out including pressure disturbances and an approximate frequency condition obtained. For positive strain the unsteady analysis indicates that the pulsating instability is suppressed. However, for a converging flow (negative strain), the instability is encouraged. Furthermore, the change of the neutral stability boundary in parameter space is explored, showing that a sharp pressure reduction makes the pulsating instability much more accessible.
No abstract is provided for this article.
This paper investigates the sparse β model with 𝓁1 penalty in the field of network data models, which is a hot topic in both statistical and social network research. We present a refined algorithm designed for parameter estimation in the proposed model. Its effectiveness is highlighted through its alignment with the proximal gradient descent method, stemming from the convexity of the loss function. We study the estimation consistency and establish an optimal bound for the proposed estimator. Empirical validations facilitated through meticulously designed simulation studies corroborate the efficacy of our methodology. These assessments highlight the prospective contributions of our methodology to the advanced field of network data analysis.
Web services commonly employ Content Distribution Networks (CDNs) for performance and security. As web traffic is becoming 100% HTTPS, more and more websites allow CDNs to terminate their HTTPS connections. This practice may expose a website's user sensitive information such as a user's login password to a third-party CDN. In this paper, we measure and quantify the extent of user password exposure to third-party CDNs. We find that among Alexa top 50K websites, at least 12,451 of them use CDNs and contain user login entrances. Among those websites, 33% of them expose users' passwords to the CDNs, and a popular CDN may observe passwords from more than 40% of its customers. This result suggests that if a CDN infrastructure has a vulnerability or an insider attack, many users' accounts will be at risk. If we assume the attacker is a passive eavesdropper, a website can avoid this vulnerability by encrypting users' passwords in HTTPS connections. Our measurement shows that less than 17% of the websites adopt this countermeasure.
Swarm intelligence based algorithms such as particle swarm optimization have become popular in the last two decades. Various new algorithms such as cuckoo search and bat algorithm also show promising efficiency. In all these algorithms, it is essential to maintain the balance of exploration and exploitation by controlling directly and indirectly the diversity of the population. Different algorithms may use different mechanisms to control such diversity. In this review paper, the author reviews and analyzes the roles of diversity and relevant mechanisms in swarm intelligence. The author also discuss parameter tuning and parameter control. In addition, the author highlights some key open questions in swarm intelligence.
Details the interdisciplinary nature of mathematical modeling and numerical algorithms. The book combines a variety of applications from diverse fields to illustrate how the methods can be used to model physical processes, design new products, find solutions to challenging problems, and increase competitiveness in international markets.
No abstract is provided for this article.
New results are derived for the stability analysis of bilinear systems (BLS) with output feedback of a general form which includes linear control functions, quadratic functions, all functions which satisfy Lipschitz condition and others. Theorems and applications are obtained for time-variant, continuous and discrete BLS. The results form a base for adaptive trajectory-tracking controllers. The sufficient conditions which are derived can be applied directly to the range of admissible controller gains for given plant parameters, or there is a trade off between controller and plant design parameters. The method does not depend on the computation of a Liapunov function and indirect stability analysis as do most techniques which are available in the literature. In the continuous case, certain necessary conditions also are derived. A field-controlled, electric motor example is presented.
Modern metaheuristic algorithms such as particle swarm optimization and cuckoo search start to demonstrate their power in dealing with tough optimization problems and even NP-hard problems. This book reviews and introduces the state-of-the-art nature-inspired metaheuristic algorithms for global optimization, including ant and bee algorithms, bat algorithm, cuckoo search, differential evolution, firefly algorithm, genetic algorithms, harmony search, particle swarm optimization, simulated annealing and support vector machines. In this revised edition, we also include how to deal with nonlinear constraints. Worked examples with implementation have been used to show how each algorithm works. This book is thus an ideal textbook for an undergraduate and/or graduate course as well as for self study. As some of the algorithms such as the cuckoo search and firefly algorithms are at the forefront of current research, this book can also serve as a reference for researchers.
