Atmospheric visibility and PM10 as indicators of new particle formation in an urban environment

It is well-known that new particle formation (NPF) in the atmosphere is inhibited by pre-existing particles in the air that act as condensation sinks to decrease the concentration and, thus, the supersaturation of precursor gases. In this study, we investigate the effects of two parameters - atmospheric visibility, expressed as the particle back-scatter coefficient (BSP), and PM10 particulate mass concentration, on the occurrences of NPF events in an urban environment where the majority of precursor gases originate from motor vehicle and industrial sources. This is the first attempt to derive direct relationships between each of these two parameters and the occurrence of NPF. NPF events were identified from data obtained with a neutral cluster and air ion spectrometer over 245 days within a calendar year. Bayesian logistic regression was used to determine the probability of observing NPF as functions of BSP and PM10. We show that the BSP at 08 h on a given day is a reliable indicator of an NPF event later that day. The posterior median probability of observing an NPF event was greater than 0.5 (95%) when the BSP at 08 h was less than 6.8 Mm-1.

Parallel processor scheduling for minimizing total weighted tardiness using ant colony optimization

In the modern business environment, meeting due dates and avoiding delay penalties are very important goals that can be accomplished by minimizing total weighted tardiness. We consider a scheduling problem in a system of parallel processors with the objective of minimizing total weighted tardiness. Our aim in the present work is to develop an efficient algorithm for solving the parallel processor problem as compared to the available heuristics in the literature and we propose the ant colony optimization approach for this problem. An extensive experimentation is conducted to evaluate the performance of the ACO approach on different problem sizes with the varied tardiness factors. Our experimentation shows that the proposed ant colony optimization algorithm is giving promising results compared to the best of the available heuristics.

Optimization models for expanding a railway’s theoretical capacity

Changing the topology of a railway network can greatly affect its capacity. Railway networks however can be altered in a multitude of different ways. As each way has significant immediate and long term financial ramifications, it is a difficult task to decide how and where to expand the network. In response some railway capacity expansion models (RCEM) have been developed to help capacity planning activities, and to remove physical bottlenecks in the current railway system. The exact purpose of these models is to decide given a fixed budget, where track duplications and track sub divisions should be made, in order to increase theoretical capacity most. These models are high level and strategic, and this is why increases to the theoretical capacity is concentrated upon. The optimization models have been applied to a case study to demonstrate their application and their worth. The case study evidently shows how automated approaches of this nature could be a formidable alternative to current manual planning techniques and simulation. If the exact effect of track duplications and sub-divisions can be sufficiently approximated, this approach will be very applicable.

The Alpha-Method Direct Transcription In Path Constrained Dynamic Optimization

Numerically discretized dynamic optimization problems having active inequality and equality path constraints that along with the dynamics induce locally high index differential algebraic equations often cause the optimizer to fail in convergence or to produce degraded control solutions. In many applications, regularization of the numerically discretized problem in direct transcription schemes by perturbing the high index path constraints helps the optimizer to converge to usefulm control solutions. For complex engineering problems with many constraints it is often difficult to find effective nondegenerat perturbations that produce useful solutions in some neighborhood of the correct solution. In this paper we describe a numerical discretization that regularizes the numerically consistent discretized dynamics and does not perturb the path constraints. For all values of the regularization parameter the discretization remains numerically consistent with the dynamics and the path constraints specified in the, original problem. The regularization is quanti. able in terms of time step size in the mesh and the regularization parameter. For full regularized systems the scheme converges linearly in time step size.The method is illustrated with examples.

Portfolio Optimization in a Semi-Markov Modulated Market

We address a portfolio optimization problem in a semi-Markov modulated market. We study both the terminal expected utility optimization on finite time horizon and the risk-sensitive portfolio optimization on finite and infinite time horizon. We obtain optimal portfolios in relevant cases. A numerical procedure is also developed to compute the optimal expected terminal utility for finite horizon problem.

Low-temperature preparation of fine-particle cobaltites

A novel solid-solution precursor method for the preparation of fine-particle cobaltites at low temperatures has been described. The precursors, hydrazinium metal hydrazine carboxylate hydrates, N2H5M1/3Co2/3(N2H3COO)3 · H2O, where M = Mg, Mn, Fe, Co, Ni, and Zn, decompose in air <250°C to yield corresponding metal cobaltites, MCo2O4. Formation of cobaltites has been confirmed by thermogravimetry (TG) weight loss, IR, and X-ray diffraction. Combustion of the precursor in air yields fine-particle cobaltites with surface areas in the range of 12–115 m2g−1 and particle sizes of 1–40 μm. Low decomposition temperatures of the precursors accompanied by the evolution of large amounts of gases appear to control the particle size of the cobaltites.

The machinability of a cast aluminium alloy-graphite particle composite

The microstructure of a cast Al---Si alloy-graphite particle composite is examined using optical and analytical scanning electron microscopy. Specimens containing different percentages of graphite were machined by orthogonal planning with 25° and 45° rake angle tools at both 6.5 and 13.2 m min−1. The machining forces are reported and the chip-rake-face friction coefficients and shear flow stresses are calculated. It is shown that the reduction in machining forces with increasing graphite content is due mostly to a decrease in the shear flow stress rather than to lower chip-rake-face friction. Both the polished and the machined surfaces of the composite are rougher than those of the simple alloy, apparently owing to the greater porosity, the tearing out of graphite particles, or the opening of cracks at the graphite particles in the wake of the tool.

A novel combustion process for the synthesis of fine particle α-alumina and related oxide materials

Synthesis of fine particle α-alumina and related oxide materials such as MgAl2O4, CaAl2O4, Y3Al5O12 (YAG), Image , β′-alumina, LaAlO3 and ruby powder (Image ) has been achieved at low temperatures (500°C) by the combustion of corresponding metal nitrate-urea mixtures. Solid combustion products have been identified by their characteristic X-ray diffraction patterns. The fine particle nature of α-alumina and related oxide materials has been investigated using SEM, TEM, particle size analysis and surface area measurements.

Performance of an Al-Si-graphite particle composite piston in a diesel engine

Al-Si-graphite particle composite alloy pistons containing different percentages of about 80 μm uncoated graphite particles were successfully cast by foundry techniques. Tests with a 5 hp single-cylinder diesel engine show that Al-Si-graphite particle composite pistons can withstand an endurance test of 500 h without any apparent deterioration and do not seize during the running-in period. The use of the Al-Si-3% graphite particle composite piston also results in (a) up to 3% reduction in the specific fuel consumption, (b) considerable reduction in the wear of all four piston rings, (c) a reduction in piston wear, (d) a 9% reduction in the frictional horsepower losses of the engine as determined by the motoring test and (e) a slight increase in the exhaust gas temperature. These reductions (a)–(d) appear to be due to increased lubrication from the graphite particles which are smeared on the bearing surface, the higher damping capacity of the composite pistons and the reduced coefficient of thermal expansion of the composite pistons. Preliminary results indicate that aluminum-graphite particle composite alloy is a promising material for automotive pistons.

Investigation of Deep Defects Due to -Particle Irradiation in n-Silicon

Electrical properties of deep defects induced in n-silicon by -particles of about 10 MeV energy at a dose of 1014 and 1015 cm-2 are studied by DLTS. The levels at Ec -0.18 eV, Ec -0.26 eV, and Ec -0.48 eV are identified as A center, V2 (=/-) and V2 (-/0) on the basis of activation energy, electron capture cross section, and annealing behavior. Two other irradiation related levels at Ec -0.28 eV and Ec -0.51 eV could not be related to any known center.

Size optimization of a cantilever beam under deformation-dependent loads with application to wheat stalks

In this paper, we consider the optimization of the cross-section profile of a cantilever beam under deformation-dependent loads. Such loads are encountered in plants and trees, cereal crop plants such as wheat and corn in particular. The wind loads acting on the grain-bearing spike of a wheat stalk vary with the orientation of the spike as the stalk bends; this bending and the ensuing change in orientation depend on the deformation of the plant under the same load.The uprooting of the wheat stalks under wind loads is an unresolved problem in genetically modified dwarf wheat stalks. Although it was thought that the dwarf varieties would acquire increased resistance to uprooting, it was found that the dwarf wheat plants selectively decreased the Young's modulus in order to be compliant. The motivation of this study is to investigate why wheat plants prefer compliant stems. We analyze this by seeking an optimal shape of the wheat plant's stem, which is modeled as a cantilever beam, by taking the large deflection of the stem into account with the help of co-rotational finite element beam modeling. The criteria considered here include minimum moment at the fixed ground support, adequate stiffness and strength, and the volume of material. The result reported here is an example of flexibility, rather than stiffness, leading to increased strength.

A genome-wide association study of Cloninger's temperament scales: implications for the evolutionary genetics of personality

Variation in personality traits is 30-60% attributed to genetic influences. Attempts to unravel these genetic influences at the molecular level have, so far, been inconclusive. We performed the first genome-wide association study of Cloninger's temperament scales in a sample of 5117 individuals, in order to identify common genetic variants underlying variation in personality. Participants' scores on Harm Avoidance, Novelty Seeking, Reward Dependence, and Persistence were tested for association with 1,252,387 genetic markers. We also performed gene-based association tests and biological pathway analyses. No genetic variants that significantly contribute to personality variation were identified, while our sample provides over 90% power to detect variants that explain only 1% of the trait variance. This indicates that individual common genetic variants of this size or greater do not contribute to personality trait variation, which has important implications regarding the genetic architecture of personality and the evolutionary mechanisms by which heritable variation is maintained.

Preparation of cast aluminium alloy-mica particle composites

The optimum conditions for producing cast aluminium alloy-mica particle composites, by stirring mica particles (40 to 120 mgrm) in molten aluminium alloys (above their liquidus temperatures), followed by casting in permanent moulds, are described. Addition of magnesium either as pieces along with mica particles on the surface of the melts or as a previously added alloying element was found to be necessary to disperse appreciable quantities (1.5 to 2 wt.%) of mica particles in the melts and retain them as uniform dispersions in castings under the conditions of present investigation. These castings can be remelted and degassed with nitrogen at least once with the retention of about 80% mica particles in the castings. Electron probe micro-analysis of these cast composites showed that magnesium added to the surface of the melt along with mica has a tendency to segregate around the mica particles, apparently improving the dispersability for mica particles in liquid aluminium alloys. The mechanical properties of the aluminium alloy-mica particle composite decrease with an increase in mica content, however, even at 2.2% the composite has a tensile strength of 14.22 kg mm–2 with 1.1% elongation, a compression strength of 42.61 kg mm–2, and an impact strength of 0.30 kgm cm–2. The properties are adequate for certain bearing applications, and the aluminium-mica composite bearings were found to run under boundary lubrication, semi-dry and dry friction conditions whereas the matrix alloy (without mica) bearings seized or showed stick slip under the same conditions.

Silvicultural decisions based on simulation-optimization systems

Forest management is facing new challenges under climate change. By adjusting thinning regimes, conventional forest management can be adapted to various objectives of utilization of forest resources, such as wood quality, forest bioenergy, and carbon sequestration. This thesis aims to develop and apply a simulation-optimization system as a tool for an interdisciplinary understanding of the interactions between wood science, forest ecology, and forest economics. In this thesis, the OptiFor software was developed for forest resources management. The OptiFor simulation-optimization system integrated the process-based growth model PipeQual, wood quality models, biomass production and carbon emission models, as well as energy wood and commercial logging models into a single optimization model. Osyczka s direct and random search algorithm was employed to identify optimal values for a set of decision variables. The numerical studies in this thesis broadened our current knowledge and understanding of the relationships between wood science, forest ecology, and forest economics. The results for timber production show that optimal thinning regimes depend on site quality and initial stand characteristics. Taking wood properties into account, our results show that increasing the intensity of thinning resulted in lower wood density and shorter fibers. The addition of nutrients accelerated volume growth, but lowered wood quality for Norway spruce. Integrating energy wood harvesting into conventional forest management showed that conventional forest management without energy wood harvesting was still superior in sparse stands of Scots pine. Energy wood from pre-commercial thinning turned out to be optimal for dense stands. When carbon balance is taken into account, our results show that changing carbon assessment methods leads to very different optimal thinning regimes and average carbon stocks. Raising the carbon price resulted in longer rotations and a higher mean annual increment, as well as a significantly higher average carbon stock over the rotation.