Evaluation of k-epsilon and RNG turbulence models for confined swirling and non-swirling flow

In a very recent study [1] the Renormalisation Group (RNG) turbulence model was used to obtain flow predictions in a strongly swirling quarl burner, and was found to perform well in predicting certain features that are not well captured using less sophisticated models of turbulence. The implication is that the RNG approach should provide an economical and reliable tool for the prediction of swirling flows in combustor and furnace geometries commonly encountered in technological applications. To test this hypothesis the present work considers flow in a model furnace for which experimental data is available [2]. The essential features of the flow which differentiate it from the previous study [1] are that the annular air jet entry is relatively narrow and the base wall of the cylindrical furnace is at 90 degrees to the inlet pipe. For swirl numbers of order 1 the resulting flow is highly complex with significant inner and outer recirculation regions. The RNG and standard k-epsilon models are used to model the flow for both swirling and non-swirling entry jets and the results compared with experimental data [2]. Near wall viscous effects are accounted for in both models via the standard wall function formulation [3]. For the RNG model, additional computations with grid placement extending well inside the near wall viscous-affected sublayer are performed in order to assess the low Reynolds number capabilities of the model.

Computation of confined swirling flow using RNG and k-epsilon turbulence models

In this work we numerically model isothermal turbulent swirling flow in a cylindrical burner. Three versions of the RNG k-epsilon model are assessed against performance of the standard k-epsilon model. Sensitivity of numerical predictions to grid refinement, differing convective differencing schemes and choice of (unknown) inlet dissipation rate, were closely scrutinised to ensure accuracy. Particular attention is paid to modelling the inlet conditions to within the range of uncertainty of the experimental data, as model predictions proved to be significantly sensitive to relatively small changes in upstream flow conditions. We also examine the characteristics of the swirl--induced recirculation zone predicted by the models over an extended range of inlet conditions. Our main findings are: - (i) the standard k-epsilon model performed best compared with experiment; - (ii) no one inlet specification can simultaneously optimize the performance of the models considered; - (iii) the RNG models predict both single-cell and double-cell IRZ characteristics, the latter both with and without additional internal stagnation points. The first finding indicates that the examined RNG modifications to the standard k-e model do not result in an improved eddy viscosity based model for the prediction of swirl flows. The second finding suggests that tuning established models for optimal performance in swirl flows a priori is not straightforward. The third finding indicates that the RNG based models exhibit a greater variety of structural behaviour, despite being of the same level of complexity as the standard k-e model. The plausibility of the predicted IRZ features are discussed in terms of known vortex breakdown phenomena.

Role of F-gravity in cosmological models

Abstract is not available.

Elements of Volatility at High Frequency

Volatility is central in options pricing and risk management. It reflects the uncertainty of investors and the inherent instability of the economy. Time series methods are among the most widely applied scientific methods to analyze and predict volatility. Very frequently sampled data contain much valuable information about the different elements of volatility and may ultimately reveal the reasons for time varying volatility. The use of such ultra-high-frequency data is common to all three essays of the dissertation. The dissertation belongs to the field of financial econometrics. The first essay uses wavelet methods to study the time-varying behavior of scaling laws and long-memory in the five-minute volatility series of Nokia on the Helsinki Stock Exchange around the burst of the IT-bubble. The essay is motivated by earlier findings which suggest that different scaling laws may apply to intraday time-scales and to larger time-scales, implying that the so-called annualized volatility depends on the data sampling frequency. The empirical results confirm the appearance of time varying long-memory and different scaling laws that, for a significant part, can be attributed to investor irrationality and to an intraday volatility periodicity called the New York effect. The findings have potentially important consequences for options pricing and risk management that commonly assume constant memory and scaling. The second essay investigates modelling the duration between trades in stock markets. Durations convoy information about investor intentions and provide an alternative view at volatility. Generalizations of standard autoregressive conditional duration (ACD) models are developed to meet needs observed in previous applications of the standard models. According to the empirical results based on data of actively traded stocks on the New York Stock Exchange and the Helsinki Stock Exchange the proposed generalization clearly outperforms the standard models and also performs well in comparison to another recently proposed alternative to the standard models. The distribution used to derive the generalization may also prove valuable in other areas of risk management. The third essay studies empirically the effect of decimalization on volatility and market microstructure noise. Decimalization refers to the change from fractional pricing to decimal pricing and it was carried out on the New York Stock Exchange in January, 2001. The methods used here are more accurate than in the earlier studies and put more weight on market microstructure. The main result is that decimalization decreased observed volatility by reducing noise variance especially for the highly active stocks. The results help risk management and market mechanism designing.

Modeling ecological and evolutionary processes in spatially structured populations

Many species inhabit fragmented landscapes, resulting either from anthropogenic or from natural processes. The ecological and evolutionary dynamics of spatially structured populations are affected by a complex interplay between endogenous and exogenous factors. The metapopulation approach, simplifying the landscape to a discrete set of patches of breeding habitat surrounded by unsuitable matrix, has become a widely applied paradigm for the study of species inhabiting highly fragmented landscapes. In this thesis, I focus on the construction of biologically realistic models and their parameterization with empirical data, with the general objective of understanding how the interactions between individuals and their spatially structured environment affect ecological and evolutionary processes in fragmented landscapes. I study two hierarchically structured model systems, which are the Glanville fritillary butterfly in the Åland Islands, and a system of two interacting aphid species in the Tvärminne archipelago, both being located in South-Western Finland. The interesting and challenging feature of both study systems is that the population dynamics occur over multiple spatial scales that are linked by various processes. My main emphasis is in the development of mathematical and statistical methodologies. For the Glanville fritillary case study, I first build a Bayesian framework for the estimation of death rates and capture probabilities from mark-recapture data, with the novelty of accounting for variation among individuals in capture probabilities and survival. I then characterize the dispersal phase of the butterflies by deriving a mathematical approximation of a diffusion-based movement model applied to a network of patches. I use the movement model as a building block to construct an individual-based evolutionary model for the Glanville fritillary butterfly metapopulation. I parameterize the evolutionary model using a pattern-oriented approach, and use it to study how the landscape structure affects the evolution of dispersal. For the aphid case study, I develop a Bayesian model of hierarchical multi-scale metapopulation dynamics, where the observed extinction and colonization rates are decomposed into intrinsic rates operating specifically at each spatial scale. In summary, I show how analytical approaches, hierarchical Bayesian methods and individual-based simulations can be used individually or in combination to tackle complex problems from many different viewpoints. In particular, hierarchical Bayesian methods provide a useful tool for decomposing ecological complexity into more tractable components.

Towards stress freezing in birefringent orthotropic composite models

Birefringent composite models are fabricated using epoxy resin reinforced with unidirectionally oriented glass fibers. The mechanical and photoelastic properties of the material at room temperature are determined. To explore the possibility of application of stress-freezing technique to birefringent composite models, the behavior and properties of this material are studied at elevated temperature (at stress-freezing temperature of the resin). The properties of the material at room and at elevated temperatures are reported. The feasibility of stress freezing glass-fiber-reinforced epoxy composites with low-fiber-volume fraction is discussed.

Role of Temperature in the Biological Activity of a Boreal Forest

In northern latitudes, temperature is the key factor driving the temporal scales of biological activity, namely the length of the growing season and the seasonal efficiency of photosynthesis. The formation of atmospheric concentrations of biogenic volatile organic compounds (BVOCs) are linked to the intensity of biological activity. However, interdisciplinary knowledge of the role of temperature in the biological processes related to the annual cycle and photosynthesis and atmospheric chemistry is not fully understood. The aim of this study was to improve understanding of the role of temperature in these three interlinked areas: 1) onset of growing season, 2) photosynthetic efficiency and 3) BVOC air concentrations in a boreal forest. The results present a cross-section of the role of temperature on different spatial (southern northern boreal), structural (tree forest stand - forest) and temporal (day-season- year) scales. The fundamental status of the Thermal Time model in predicting the onset of spring recovery was confirmed. However, it was recommended that sequential models would be more appropriate tools when the onset of the growing season is estimated under a warmer climate. A similar type of relationship between photosynthetic efficiency and temperature history was found in both southern and northern boreal forest stands. This result draws attention to the critical question of the seasonal efficiency of coniferous species to emit organic compounds under a warmer climate. New knowledge about the temperature dependence of the concentrations of biogenic volatile organic compounds in a boreal forest stand was obtained. The seasonal progress and the inter-correlation of BVOC concentrations in ambient air indicated a link to biological activity. Temperature was found to be the main driving factor for the concentrations. However, in addition to temperature, other factors may play a significant role here, especially when the peak concentrations are studied. There is strong evidence that the spring recovery and phenological events of many plant species have already advanced in Europe. This study does not fully support this observation. In a boreal forest, changes in the annual cycle, especially the temperature requirement in winter, would have an impact on the atmospheric BVOC composition. According to this study, more joint phenological and BVOC field observations and laboratory experiments are still needed to improve these scenarios.

Deformation and stability regression models for soil nail walls

Lateral displacement and global stability are the two main stability criteria for soil nail walls. Conventional design methods do not adequately address the deformation behaviour of soil nail walls, owing to the complexity involved in handling a large number of influencing factors. Consequently, limited methods of deformation estimates based on empirical relationships and in situ performance monitoring are available in the literature. It is therefore desirable that numerical techniques and statistical methods are used in order to gain a better insight into the deformation behaviour of soil nail walls. In the present study numerical experiments are conducted using a 2 4 factorial design method. Based on analysis of the maximum lateral deformation and factor-of-safety observations from the numerical experiments, regression models for maximum lateral deformation and factor-of-safety prediction are developed and checked for adequacy. Selection of suitable design factors for the 2 4 factorial design of numerical experiments enabled the use of the proposed regression models over a practical range of soil nail wall heights and in situ soil variability. It is evident from the model adequacy analyses and illustrative example that the proposed regression models provided a reasonably good estimate of the lateral deformation and global factor of safety of the soil nail walls.

Modeling of Convection and Macrosegregation through Appropriate Consideration of Multiphase/Multiscale Phenomena during Alloy Solidification

Solidification processes are complex in nature, involving multiple phases and several length scales. The properties of solidified products are dictated by the microstructure, the mactostructure, and various defects present in the casting. These, in turn, are governed by the multiphase transport phenomena Occurring at different length scales. In order to control and improve the quality of cast products, it is important to have a thorough understanding of various physical and physicochemical phenomena Occurring at various length scales. preferably through predictive models and controlled experiments. In this context, the modeling of transport phenomena during alloy solidification has evolved over the last few decades due to the complex multiscale nature of the problem. Despite this, a model accounting for all the important length scales directly is computationally prohibitive. Thus, in the past, single-phase continuum models have often been employed with respect to a single length scale to model solidification processing. However, continuous development in understanding the physics of solidification at various length scales oil one hand and the phenomenal growth of computational power oil the other have allowed researchers to use increasingly complex multiphase/multiscale models in recent. times. These models have allowed greater understanding of the coupled micro/macro nature of the process and have made it possible to predict solute segregation and microstructure evolution at different length scales. In this paper, a brief overview of the current status of modeling of convection and macrosegregation in alloy solidification processing is presented.

The ecology of the mountain hare (Lepus timidus L.) in managed boreal forests: habitat associations at different forest scales

Aims of this thesis This study is part of a larger hare project in Finland, which provides answers to basic ecological questions regarding the mountain hare. This study of the ecology of the mountain hare focuses in particular on different levels of managed boreal forest. The feeding habits and intensity of mountain hares in winter are explored, and the connections between mountain hares versus the forest structure are also studied (e.g. habitat use and the importance of different forest layers for hares). The use of the environment by hares at the landscape level was examined (forest patch structures), and the home ranges of mountain hares were studied. Finally, the productivity and survival rate of mountain hare populations were also studied (discussion e.g. predator effects on hare populations). Conclusions Feeding intensity seemed to be highest in the spring-winter, when home ranges were also largest. Favourable food species are covered by snow in winter and the mobility of hares is highest during late winter. A shortage of suitable food species may be problematic for hares, especially during the winter period. In this study mountain hares preferred a dense shrub layer at local level and deciduous and mixed tree forest over coniferous forest at the landscape level. Food and shelter are vital for hares and the preference for particular habitats may also affect the population dynamics of the mountain hare. It would be possible to improve the quality of food and shelter or at least prevent the most negative habitat changes through forest management. At a local level it is also possible to add supplementary food for hares through the winter period. The intensive clearing of young sapling stands and especially the removal of deciduous shrubs and trees reduces the quality of habitats for the mountain hare. Mountain hares primarily live in forest habitat and it is possible that changes in the forest structure play a crucial role in mountain hare habitat preference. Ecological knowledge of the mountain hare is vital to create habitat structure more suitable for the species. More deciduous trees should be saved in managing forests and the mechanical clearing of the shrub layer should be done carefully.

Comprehensive view of the combustion models of composite solid propellants

Abstrat is not available.

Cellular Automata Models of Traffic Behavior in Presence of Speed Breaking Structures

In this article, we study traffic flow in the presence of speed breaking structures. The speed breakers are typically used to reduce the local speed of vehicles near certain institutions such as schools and hospitals. Through a cellular automata model we study the impact of such structures on global traffic characteristics. The simulation results indicate that the presence of speed breakers could reduce the global flow under moderate global densities. However, under low and high global density traffic regime the presence of speed breakers does not have an impact on the global flow. Further the speed limit enforced by the speed breaker creates a phase distinction. For a given global density and slowdown probability, as the speed limit enforced by the speed breaker increases, the traffic moves from the reduced flow phase to maximum flow phase. This underlines the importance of proper design of these structures to avoid undesired flow restrictions.

Impacts of agriculture on amphibians at multiple scales

Agriculture-mediated habitat loss and degradation together with climate change are among the greatest global threats to species, communities, and ecosystem functioning. During the last century, more than 50% of the world's wetlands have been lost and agricultural activities have subjected wetland species to increased isolation and decreased quality of habitats. Likewise, as a part of agricultural intensification, the use of pesticides has increased notably, and pesticide residues occur frequently in wetlands making the exposure of wetland organisms to pesticides highly probable. In this thesis, a set of ecotoxicological and landscape ecological studies were carried out to investigate pesticide-effects on tadpoles, and species-habitat relationships of amphibians in agricultural landscapes. The results show that the fitness of R. temporaria tadpoles can be negatively affected by sublethal pesticide concentrations, and that pesticides may increase the costs of response to natural environmental stressors. However, tadpoles may also be able to compensate for some of the negative effects of pesticides. The results further demonstrate that both historic and current-day agricultural land use can negatively impact amphibians, but that in some cases the costs of living in agricultural habitats may only become apparent when amphibians face other environmental stressors, such as drought. Habitat heterogeneity may, however, increase the persistence of amphibians in agricultural landscapes. Hence, the results suggest that amphibians are likely to be affected by agricultural processes that operate at several spatial and temporal scales, and that it is probable that various processes related to current-day agriculture will affect both larval and adult amphibians. The results imply that maintaining dense wetland patterns could enhance persistence of amphibian populations in agricultural habitats, and indicate that heterogeneous landscapes may lower the risk of regional amphibian population declines under extreme weather perturbations.

NUVIEW:software for display and interactive manipulation of nucleic acid models

The NUVIEW software package allows skeletal models of any double helical nucleic acid molecule to be displayed out a graphics monitor and to apply various rotations, translations and scaling transformations interactively, through the keyboard. The skeletal model is generated by connecting any pair of representative points, one from each of the bases in the basepair. In addition to the above mentioned manipulations, the base residues can be identified by using a locator and the distance between any pair of residues can be obtained. A sequence based color coded display allows easy identification of sequence repeats, such as runs of Adenines. The real time interactive manipulation of such skeletal models for large DNA/RNA double helices, can be used to trace the path of the nucleic acid chain in three dimensions and hence get a better idea of its topology, location of linear or curved regions, distances between far off regions in the sequence etc. A physical picture of these features will assist in understanding the relationship between base sequence, structure and biological function in nucleic acids.