On periodically isotonic climate change

In a view of the past two millennia, is the recent 160-year global warmth an anomaly or a continuation of past climate pattern? In this work, we present two non-parametric χ² tests based on the U-test for the isotonic change-point problem proposed in an unpublished work by G. Shen and H. Xu (henceforth abbreviated as SX (unpublished)) and apply them to the global warming data. Our tests do not require any structure assumption on the underlying the deterministic mean process {μ_t} under the periodically isotonic alternative, but accommodate a large class of the models for the random error process. Being more attractive, the two tests obviate estimation of {μ_t} and possess explicit asymptotic distributions for short-range dependence data, and have asymptotic power 1 even under the local alternative.     

An efficient linear model and optimisation algorithm for multi-site combined heat and power production

Combined heat and power (CHP) production is an important energy production technology which can help to improve the efficiency of energy production and to reduce the emission of CO₂. Cost-efficient operation of a CHP system can be planned using an optimisation model based on hourly load forecasts. A long-term planning model decomposes into hourly models, which can be formulated as linear programming (LP) problems. Such problems can be solved efficiently using the specialized Power Simplex algorithm. However, Power Simplex can only manage one heat and one power balance. Since heat cannot be transported over long distances, Power Simplex applies only for local CHP planning.In this paper we formulate the hourly multi-site CHP planning problem with multiple heat balances as an LP model with a special structure. We then develop the Extended Power Simplex (EPS) algorithm for solving such models efficiently. Even though the problem can be quite large as the number of demand sites increases, EPS demonstrates very good efficiency. In test runs with realistic models, EPS is from 29 to 85 times faster than an efficient sparse Simplex code using the product form of inverse (PFI). Furthermore, the relative efficiency of EPS improves as the problem size grows.     

Three-dimensional modelling of NOx and particulate traps using CFD: A porous medium approach

Lean burn after-treatment systems are the current focus for reducing emissions from diesel exhaust. The trend is for commercial CFD packages to use a single channel modelling approach. Due to computational demands, this necessitates specification of representative channels for modelling, implying prior knowledge of the flow field. This paper investigates a methodology for applying the porous medium approach to lean burn after-treatment systems. This approach has proved successful for three-way catalysis modelling and has the advantage that the flow field is predicted. Chemical kinetic rates for NO_x trapping and regeneration in the model are based on information available in the open literature. Similarly, filtration information based on mass accumulation and soot combustion kinetics are also readily available. Modification of the source terms in a commercial CFD package enables prediction of trapping and release of NO_x. This is an effective way to model a NO_x trap after-treatment system and provides simultaneous 3D modelling of the flow field. With diesel, particulate filtration is required. In the case of particulate traps, however, because of channel geometry, some assumptions are necessary for use of the porous medium approach and these are discussed in this paper. Both models produce qualitatively correct output and have parameters that can be tuned to conform to experimental data. Data to validate the NO_x trap model is to be measured. The particulate trap model, on the other hand, is a feasibility study for modelling the complete diesel after-treatment system using the porous medium approach.     

Empirical Mark Covariance and Product Density Function of Stationary Marked Point Processes—A Survey on Asymptotic Results

Marked point processes are stochastic models to describe random patterns of marked points {[X _i ,M _i ], i?≥?1} in some bounded subset of the d-dimensional Euclidean space (usually d?=?1, 2 or 3 in applications), where each point X _i carries additional random information expressed as mark M _i taking values in some metric space. To study the correlations between distinct points and between marks located at distinct points we use kernel-type estimators of the second-order product density and the mark covariance function of a spatially homogeneous marked point process. Both functions and their empirical counterparts are suitable characteristics to identify point process models by construction of statistical goodness-of-fit tests.     

Applications of?the Cosecant and Related Numbers

Power series expansions for cosecant and related functions together with a vast number of applications stemming from their coefficients are derived here. The coefficients for the cosecant expansion can be evaluated by using: (1) numerous recurrence relations, (2) expressions resulting from the application of the partition method for obtaining a power series expansion and (3) the result given in Theorem 3. Unlike the related Bernoulli numbers, these rational coefficients, which are called the cosecant numbers and are denoted by c _k , converge rapidly to zero as k????. It is then shown how recent advances in obtaining meaningful values from divergent series can be modified to determine exact numerical results from the asymptotic series derived from the Laplace transform of the power series expansion for tcsc?(at). Next the power series expansion for secant is derived in terms of related coefficients known as the secant numbers d _k . These numbers are related to the Euler numbers and can also be evaluated by numerous recurrence relations, some of which involve the cosecant numbers. The approaches used to obtain the power series expansions for these fundamental trigonometric functions in addition to the methods used to evaluate their coefficients are employed in the derivation of power series expansions for integer powers and arbitrary powers of the trigonometric functions. Recurrence relations are of limited benefit when evaluating the coefficients in the case of arbitrary powers. Consequently, power series expansions for the Legendre-Jacobi elliptic integrals can only be obtained by the partition method for a power series expansion. Since the Bernoulli and Euler numbers give rise to polynomials from exponential generating functions, it is shown that the cosecant and secant numbers gives rise to their own polynomials from trigonometric generating functions. As expected, the new polynomials are related to the Bernoulli and Euler polynomials, but they are found to possess far more interesting properties, primarily due to the convergence of the coefficients. One interesting application of the new polynomials is the re-interpretation of the Euler-Maclaurin summation formula, which yields a new regularisation formula.     

On the KŁR conjecture in random graphs

The K?R conjecture of Kohayakawa, ?uczak, and Rödl is a statement that allows one to prove that asymptotically almost surely all subgraphs of the random graph G _n,p , for sufficiently large p:= p(n), satisfy an embedding lemma which complements the sparse regularity lemma of Kohayakawa and Rödl. We prove a variant of this conjecture which is sufficient for most known applications to random graphs. In particular, our result implies a number of recent probabilistic versions, due to Conlon, Gowers, and Schacht, of classical extremal combinatorial theorems. We also discuss several further applications.     

Comparison of turbulence models in simulating swirling pipe flows

Swirling flow is a common phenomenon in engineering applications. A numerical study of the swirling flow inside a straight pipe was carried out in the present work with the aid of the commercial CFD code fluent. Two-dimensional simulations were performed, and two turbulence models were used, namely, the RNG k–ε model and the Reynolds stress model. Results at various swirl numbers were obtained and compared with available experimental data to determine if the numerical method is valid when modeling swirling flows. It has been shown that the RNG k–ε model is in better agreement with experimental velocity profiles for low swirl, while the Reynolds stress model becomes more appropriate as the swirl is increased. However, both turbulence models predict an unrealistic decay of the turbulence quantities for the flows considered here, indicating the inadequacy of such models in simulating developing pipe flows with swirl.     

Evaluating the impact of average cost based contracts on the industrial sector in the European emission trading scheme

The inception of the emission trading scheme in Europe has contributed to power price increases. Energy intensive industries have reacted by arguing that this may affect their competitiveness and will induce them to leave Europe. Taking up a proposal of these industrial sectors, we explore the possible application of special contracts, where electricity is sold at average generation cost to mitigate the impact of CO₂ cost on power prices. The model supposes fixed generation capacities. We first consider a reference model representing a perfectly competitive market where all consumers (industries and the rest of the market) are price-takers and buy electricity at short-run marginal cost. We then change the market design by assuming that energy intensive industries pay power either at a regional or at a zonal average cost price. The analysis is conducted with simulation models applied to the Central Western European power market. The models are implemented in GAMS/PATH. This work has been financially supported by the Chair Lhoist Berghmans in Environmental Economics and Management and by the Italian project PRIN 2006, Generalized monotonicity: models and applications, whose national responsible is Prof. Elisabetta Allevi.     

p-adic physics below and above planck scales

We present a review and also new possible applications of p-adic numbers to pre-space-time physics. It is shown that instead of the extension IRⁿ → Q_pⁿ, which is usually implied in p-adic quantum field theory, it is possible to build a model based on the IRⁿ → Q_p, where p=n+2 extension and get rid of loop divergences. It is also shown that the concept of mass naturally arises in p-adic models as inverse transition probability with a dimensional constant of proportionality.     

Local clustering coefficients in preferential attachment models

The local clustering coefficients of preferential attachment models are analyzed. Previously, a general approach to preferential attachment was proposed (the PA-class was introduced); it was shown that the degree distribution in all models of the PA-class obeys a power law. The global clustering coefficient was also analyzed, and a lower bound for the mean local clustering coefficient was found. In the paper, new results are obtained by analyzing the local clustering coefficients of models of the PA-class. Namely, the behavior of the mean value C ₂(n, d) of local clustering over vertices of degree d is studied.     

A 3-D coupled Smoothed Particle Hydrodynamics and Coarse-Grained model to simulate drying mechanisms of small cell aggregates

Recently, meshfree-based computational modelling approaches have become popular in modelling biological phenomena due to their superior ability to simulate large deformations, multiphase phenomena and complex physics compared to the conventional grid-based methods. In this article, small plant cell aggregates were simulated using a three dimensional (3-D) Smoothed Particle Hydrodynamics (SPH) and Coarse-Grained (CG) coupled computational approach to predict the morphological behaviour during drying. The model predictions of these cell aggregate models have been compared qualitatively and quantitatively through comparisons with experimental findings. The results show that the shrinkage and wrinkling behaviour of cell cluster models are in fairly good agreement with real cellular structures. The agreement between the cell aggregate model predictions and the experimental findings are closer in the high and medium moisture content values (X/X₀ ≥ 0.3), than highly dried stages (X/X₀ < 0.3). Further, optimisation and sensitivity studies have been conducted on model parameters such as particle resolution, smoothing length, mass transfer characteristics and wall forces. Overall, the 3-D nature of this model allows it to predict real 3-D morphological changes more realistically compared to the previous meshfree based 2-D cellular drying models. The proposed 3-D modelling approach has a higher potential to be used to model larger plant tissues with complicated physical and mechanical interactions as well as their multiscale interactions.     

Stability of command economies

We consider the impact of fluctuations in the technology matrix A on two command input- output models. In the first, resources and goals are fixed and the model is solved for industrial production. If the growth rate can be zero, expected values of fluctuations of industrial goods are infinite. In the second, produced goods are scaled down to fit resources. Here we derive a criterion that

$\text{2log n}\text{k}$

should be small, where k is the number of significant ingredients in a good efficiency of aggregated economies, with n replaced by n₁/2 where n₁ is the number of goods aggregated into one.     

Genetic algorithms applied to computationally difficult set covering problems

The set covering problem is a known NP-hard combinatorial optimisation problem for covering the rows of a matrix by a subset of columns at minimum cost. Genetic algorithms (GA) are a class of iteration procedures that simulate the evolution process of a structured population. The objective of this work is to show that a somewhat classical GA implementation reaches high quality computational results for difficult set covering problems arising in computing the 1-width of incidence matrices of Steiner triple systems. In computational tests all optimal and best known solutions were found for incidence matrices A₉, A₁₅, A₂₇, A₄₅, A₈₁ and A₂₄₃ with reasonable times for a microcomputer implementation. Other tests with classical set covering problems confirm the good results for an additional class of instances.     

Generalised 2-circulant inequalities for the max-cut problem

The max-cut problem is a fundamental combinatorial optimisation problem, with many applications. Poljak and Turzik found some facet-defining inequalities for the associated polytope, which we call 2-circulant inequalities. We present a more general family of facet-defining inequalities, an exact separation algorithm that runs in polynomial time, and some computational results.     

Room squares with super-simple property

Constant-composition codes are a special type of constant-weight codes and have attracted recent interest due to their numerous applications. In a recent work, the authors found that an optimal (n, 5, [2, 1, 1])₄-code of constant-composition can be obtained from a Room square of side n with super-simple property. In this paper, we study the existence problem of super-simple Room squares. The problem is solved leaving only two minimal possible n undetermined.     

Existence of many L∞,λ-equivalent,non- isomorphic models of T of power λ

Suppose T is not superstable, T ⊆ T₁ (both first-order theories). If λ>∥T₁∥ is regular or strong limit, we construct 2^λ non-isomorphic, pairwise L_∞,λ-equivalent models of T of power λ, which are reducts of models of T₁. Note, however, that the proof applies to the class of models of T, T (superstable but) with dop or otop and even to appropriate non-elementary classes as well.     

Karhunen-Loeve expansions for the m-th order detrended Brownian motion

The m-th order detrended Brownian motion is defined as the orthogonal component of projection of the standard Brownian motion onto the subspace spanned by polynomials of degree up to m. We obtain the Karhunen-Loeve expansion for the process and establish a connection with the generalized (m-th order) Brownian bridge developed by MacNeill (1978) in the study of distributions of polynomial regression. The resulting distribution identity is also verified by a stochastic Fubini approach. As applications, large and small deviation asymptotic behaviors for the L ₂ norm are given.     

CFD studies on burner secondary airflow

In many fossil power plants operating today, there is insufficient means to assure the proper balancing of the secondary airflows between the individual burners of wall-fired units. This mismatch leads to decreased boiler efficiency and increased emissions. In this study, a computational fluid dynamics (CFD) modeling of a fossil power plant wind box was performed. The model solved the three-dimensional Reynolds averaged Navier–Stokes equations with the k–ε turbulence model. The CFD results were validated by the experimental data taken from a 1/8th scale model of a wall-fired fossil unit. Simulations under various mass flow rates specified at inlet, various baffle positions and two opening conditions of the burners were obtained to identify the optimum design in terms of the equalization of the secondary airflow through the burners. This study demonstrated that the combination of experimental and CFD approach can be an effective tool in the research of burner secondary airflow balancing.