American Electric Power

The Encyclopedia of Global Warming and Climate Change helps readers learn about the astonishingly intricate processes that make ours the only planet known to be habitable. These three volumes include more than 750 articles that explore major topics related to global warming and climate change—ranging geographically from the North Pole to the South Pole, and thematically from social effects to scientific causes

Attribution of Global Warming

The Encyclopedia of Global Warming and Climate Change helps readers learn about the astonishingly intricate processes that make ours the only planet known to be habitable. These three volumes include more than 750 articles that explore major topics related to global warming and climate change—ranging geographically from the North Pole to the South Pole, and thematically from social effects to scientific causes

Carbon Permits

The Encyclopedia of Global Warming and Climate Change helps readers learn about the astonishingly intricate processes that make ours the only planet known to be habitable. These three volumes include more than 750 articles that explore major topics related to global warming and climate change—ranging geographically from the North Pole to the South Pole, and thematically from social effects to scientific causes

Parallel algorithm with spectral convergence for nonlinear integro-differential equations

We discuss a numerical algorithm for solving nonlinear integro-differential equations, and illustrate our findings for the particular case of Volterra type equations. The algorithm combines a perturbation approach meant to render a linearized version of the problem and a spectral method where unknown functions are expanded in terms of Chebyshev polynomials (El-gendi's method). This approach is shown to be suitable for the calculation of two-point Green functions required in next to leading order studies of time-dependent quantum field theory.Comment: 15 pages, 9 figure

A new diagrammatic representation for correlation functions in the in-in formalism

In this paper we provide an alternative method to compute correlation functions in the in-in formalism, with a modified set of Feynman rules to compute loop corrections. The diagrammatic expansion is based on an iterative solution of the equation of motion for the quantum operators with only retarded propagators, which makes each diagram intrinsically local (whereas in the standard case locality is the result of several cancellations) and endowed with a straightforward physical interpretation. While the final result is strictly equivalent, as a bonus the formulation presented here also contains less graphs than other diagrammatic approaches to in-in correlation functions. Our method is particularly suitable for applications to cosmology.Comment: 14 pages, matches the published version. includes a modified version of axodraw.sty that works with the Revtex4 clas

Predicting gas-flow distribution in pilot-scale fluidized beds using cfd simulations

Bubbling fluidized beds are used extensively in energy and chemical industries because of their excellent heat and mass transfer characteristics. Recently, CFD has been identified as a useful tool for predicting reactor performance, but application to large scales continues to be challenging because of limitations on computational resources. Given that the hydrodynamics can largely be characterized by bubbles rising through the bed, a more feasible approach for investigating large-scale reactors is to quantify bubble dynamics and specifically, gas distribution in different phases- visible bubble flow, bubble-through flow and dense-phase flow. In this study, 3D CFD simulations of bubbling fluidized beds are first conducted to establish the impact of scale (bed diameter) on the hydrodynamics. Using solids circulation and bubble statistics (1), it is established that wall effects cease to be significant in beds larger than 50 cm (bed aspect ratio less than 1). At this scale, simulations are then carried out for two distinct Geldart B particles and data is subsequently analyzed for gas-flow distribution in the bed. Bubble statistics are also compared with existing correlations and their relation to solids circulation and mixing is investigated. The physical model and numerical tool were developed and validated in previous studies (1,2), while 3D Bubble statistics are computed using MS3DATA (Multiphase Statistics using 3D Detection and Tracking Algorithm) (3). Accurate description of the gas-flow is crucial for large-scale combustor design since quantifying gas distribution will indicate both fuel rich zones as well as oxidant bypass through bubbles leading to inefficient performance. Please click Additional Files below to see the full abstract

Sighting of critically endangered Red-headed vulture Sarcogyps calvus (Scopoli, 1786) in Palamau Tiger Reserve, Jharkhand, India

No Abstrac

Plasma And Cold Sprayed Aluminum Carbon Nanotube Composites: Quantification Of Nanotube Distribution And Multi-Scale Mechanical Properties

Carbon nanotubes (CNT) could serve as potential reinforcement for metal matrix composites for improved mechanical properties. However dispersion of carbon nanotubes (CNT) in the matrix has been a longstanding problem, since they tend to form clusters to minimize their surface area. The aim of this study was to use plasma and cold spraying techniques to synthesize CNT reinforced aluminum composite with improved dispersion and to quantify the degree of CNT dispersion as it influences the mechanical properties. Novel method of spray drying was used to disperse CNTs in Al-12 wt.% Si pre-alloyed powder, which was used as feedstock for plasma and cold spraying. A new method for quantification of CNT distribution was developed. Two parameters for CNT dispersion quantification, namely Dispersion parameter (DP) and Clustering Parameter (CP) have been proposed based on the image analysis and distance between the centers of CNTs. Nanomechanical properties were correlated with the dispersion of CNTs in the microstructure. Coating microstructure evolution has been discussed in terms of splat formation, deformation and damage of CNTs and CNT/matrix interface. Effect of Si and CNT content on the reaction at CNT/matrix interface was thermodynamically and kinetically studied. A pseudo phase diagram was computed which predicts the interfacial carbide for reaction between CNT and Al-Si alloy at processing temperature. Kinetic aspects showed that Al4C3 forms with Al-12 wt.% Si alloy while SiC forms with Al-23wt.% Si alloy. Mechanical properties at nano, micro and macro-scale were evaluated using nanoindentation and nanoscratch, microindentation and bulk tensile testing respectively. Nano and micro-scale mechanical properties (elastic modulus, hardness and yield strength) displayed improvement whereas macro-scale mechanical properties were poor. The inversion of the mechanical properties at different scale length was attributed to the porosity, CNT clustering, CNT-splat adhesion and Al4C3 formation at the CNT/matrix interface. The Dispersion parameter (DP) was more sensitive than Clustering parameter (CP) in measuring degree of CNT distribution in the matrix

Bayesian Estimation Via Sequential Monte Carlo Sampling-Constrained Dynamic Systems

Nonlinear and non-Gaussian processes with constraints are commonly encountered in dynamic estimation problems. Methods for solving such problems either ignore the constraints or rely on crude approximations of the model or probability distributions. Such approximations may reduce the accuracy of the estimates since they often fail to capture the variety of probability distributions encountered in constrained linear and nonlinear dynamic systems. This article describes a practical approach that overcomes these shortcomings via a novel extension of sequential Monte Carlo (SMC) sampling or particle filtering. Inequality constraints are imposed by accept/reject steps in the algorithm. The proposed approach provides samples representing the posterior distribution at each time point, and is shown to satisfy the same theoretical properties as unconstrained SMC. Illustrative examples show that results of the proposed approach are at least as accurate as moving horizon estimation, but computationally more efficient and in addition, the approach indicates the uncertainty associated with these estimates