Diurnal variation of atmospheric CO2 concentration and delta C-13 in an urban atmosphere during winter-role of the Nocturnal Boundary Layer

The paper presents the importance of the Nocturnal Boundary Layer in driving the diurnal variability of the atmospheric CO2 mixing ratio and the carbon isotope ratio at ground level from an urban station in India. Our observations are the first of their kind from this region. The atmospheric CO2 mixing ratio and the carbon isotopic ratio were measured for both the morning (05:30-07:30 IST) and afternoon time (16:00-18:00 IST) air samples at 5 m above ground level in Bangalore city, Karnataka State (12 degrees 58' N, 77 degrees 38' E, masl = 920 m) for a 10 day period during the winter of 2008. We observed a change of similar to 7% the in CO2 mixing ratio between the morning and afternoon time air samples. A stable isotope analysis of CO2 from morning samples showed a depletion in the carbon isotope ratio by similar to 2 parts per thousand compared to the afternoon samples. Along with the ground-based measurement of air samples, data of radiosonde measurements were also obtained from the Indian Meteorological Department to identify the vertical atmospheric structure at different time in a day. We proposed the presence or absence of the NBL as a controlling factor for the observed variability in the mixing ratio as well as its isotopic composition. Here we used the Keeling model approach to find out the carbon isotope ratio for the local sources. The local sources have further been characterized as anthropogenic and biological respiration (in %) using a two-component mixing model. We also used a vertical mixing model based on the concept of the mixing of isotopically depleted (carbon isotope) ``polluted air'' (PA) with isotopically enriched ``free atmospheric air'' (FA) above. Using this modeling approach, the contribution of FA at ground level is being estimated for both the morning and afternoon time air samples.

Field emission properties of carbon nanotube arrays with defects and impurities

Field emission from carbon nanotubes (CNTs) in the form of arrays or thin films give rise to several strongly correlated process of electromechanical interaction and degradation. Such processes are mainly due to (1) electron-phonon interaction (2) electromechanical force field leading to stretching of CNTs (3) ballistic transport induced thermal spikes, coupled with high dynamic stress, leading to degradation of emission performance at the device scale. Fairly detailed physics based models of CNTs considering the aspects (1) and (2) above have already been developed by these authors, and numerical results indicate good agreement with experimental results. What is missing in such a system level modeling approach is the incorporation of structural defects and vacancies or charge impurities. This is a practical and important problem due to the fact that degradation of field emission performance is indeed observed in experimental I-V curves. What is not clear from these experiments is whether such degradation in the I-V response is due to dynamic reorientation of the CNTs or due to the defects or due to both of these effects combined. Non-equilibrium Green’s function based simulations using a tight-binding Hamiltonian for single CNT segment show up the localization of carrier density at various locations of the CNTs. About 11% decrease in the drive current with steady difference in the drain current in the range of 0.2-0.4V of the gate voltage was reported in literature when negative charge impurity was introduced at various locations of the CNT over a length of ~20nm. In the context of field emission from CNT tips, a simplistic estimate of defects have been introduced by a correction factor in the Fowler-Nordheim formulae. However, a more detailed physics based treatment is required, while at the same time the device-scale simulation is necessary. The novelty of our present approach is the following. We employ a concept of effective stiffness degradation for segments of CNTs, which is due to structural defects, and subsequently, we incorporate the vacancy defects and charge impurity effects in the Green’s function based approach. Field emission induced current-voltage characteristics of a vertically aligned CNT array on a Cu-Cr substrate is then simulated using a detailed nonlinear mechanistic model of CNTs coupled with quantum hydrodynamics. An array of 10 vertically aligned and each 12 m long CNTs is considered for the device scale analysis. Defect regions are introduced randomly over the CNT length. The result shows the decrease in the longitudinal strain due to defects. Contrary to the expected influence of purely mechanical degradation, this result indicates that the charge impurity and hence weaker transport can lead to a different electromechanical force field, which ultimately can reduce the strain. However, there could be significant fluctuation in such strain field due to electron-phonon coupling. The effect of such fluctuations (with defects) is clearly evident in the field emission current history. The average current also decreases significantly due to such defects.

Hydrodynamic energy harvesting using an ionic polymer-metal composite stack for underwater applications

Ionic Polymer Metal Composites (IPMCs) are a class of Electro-Active Polymers (EAPs) consisting of a base polymer (usually Nafion), sandwiched between thin films of electrodes and an electrolyte. Apart from fuel cell like proton exchange process in Nafion, these IPMCs can act both as an actuator and a sensor. Typically, IPMCs have been known for their applications in fuel cell technology and in artificial muscles for robots. However, more recently, sensing properties of IPMC have opened up possibilities of mechanical energy harvesting. In this paper, we consider a bi-layer stack of IPMC membranes where fluid flow induced cyclic oscillation allows collection of electronic charge across a pair of functionalized electrode on the surface of IPMC layers/stacks. IPMCs work well in hydrated environment; more specifically, in presence of an electrolyte, and therefore, have great potential in underwater applications like hydrodynamic energy harvesting. Hydrodynamic forces produce bending deformation, which can induce transport of cations via polymer chains of the base polymer of Nafion or PTFE. In our experimental set-up, the deformation is induced into the array of IPMC membranes immersed in electrolyte by water waves caused by a plunger connected to a stepper motor. The frequency and amplitude of the water waves is controlled by the stepper motor through a micro-controller. The generated electric power is measured across a resistive load. Few orders of magnitude increase in the harvested power density is observed. Analytical modeling approach used for power and efficiency calculations are discussed. The observed electro-mechanical performance promises a host of underwater energy harvesting applications.

Validation based sparse Gaussian processes for ordinal regression

This paper proposes a sparse modeling approach to solve ordinal regression problems using Gaussian processes (GP). Designing a sparse GP model is important from training time and inference time viewpoints. We first propose a variant of the Gaussian process ordinal regression (GPOR) approach, leave-one-out GPOR (LOO-GPOR). It performs model selection using the leave-one-out cross-validation (LOO-CV) technique. We then provide an approach to design a sparse model for GPOR. The sparse GPOR model reduces computational time and storage requirements. Further, it provides faster inference. We compare the proposed approaches with the state-of-the-art GPOR approach on some benchmark data sets. Experimental results show that the proposed approaches are competitive.

Thermal Efficiency of LPG and PNG-fired burners: Experimental and numerical studies

In the present work, the thermal efficiency of a conventional domestic burner is studied both experimentally and numerically for liquefied petroleum gas (LPG) and piped natural gas (PNG) fuels. Three-dimensional computational fluid dynamic (CFD) modeling of the steady-state flow, combustion and heat transfer to the vessel is reported for the first time in such burners. Based on the insights from the CFD model concerning the flow and heat transfer, design modifications in the form of a circular insert and a radiant sheet are proposed which are observed to increase thermal efficiency for LPG. For PNG, predictions showed that loading height was a much more important factor affecting efficiency than these design modifications and an optimal loading height could be identified. Experiments confirm these trends by showing an improvement in burner thermal efficiency of 2.5% for LPG with the modified design, and 10% for PNG with the optimal loading height, demonstrating that the CFD modeling approach developed in the present work is a useful tool to study domestic burners. (C) 2013 Elsevier Ltd. All rights reserved.

Modeling of the cooling process on the runout table of a hot strip mill - A parallel approach

This paper deals with the development of a new model for the cooling process on the runout table of hot strip mills, The suitability of different numerical methods for the solution of the proposed model equation from the point of view of accuracy and computation time are studied, Parallel solutions for the model equation are proposed.

Modeling of nonreacting and reacting turbulent spray jets using a fully stochastic separated flow approach

Numerical modeling of several turbulent nonreacting and reacting spray jets is carried out using a fully stochastic separated flow (FSSF) approach. As is widely used, the carrier-phase is considered in an Eulerian framework, while the dispersed phase is tracked in a Lagrangian framework following the stochastic separated flow (SSF) model. Various interactions between the two phases are taken into account by means of two-way coupling. Spray evaporation is described using a thermal model with an infinite conductivity in the liquid phase. The gas-phase turbulence terms are closed using the k-epsilon model. A novel mixture fraction based approach is used to stochastically model the fluctuating temperature and composition in the gas phase and these are then used to refine the estimates of the heat and mass transfer rates between the droplets and the surrounding gas-phase. In classical SSF (CSSF) methods, stochastic fluctuations of only the gas-phase velocity are modeled. Successful implementation of the FSSF approach to turbulent nonreacting and reacting spray jets is demonstrated. Results are compared against experimental measurements as well as with predictions using the CSSF approach for both nonreacting and reacting spray jets. The FSSF approach shows little difference from the CSSF predictions for nonreacting spray jets but differences are significant for reacting spray jets. In general, the FSSF approach gives good predictions of the flame length and structure but further improvements in modeling may be needed to improve the accuracy of some details of the Predictions. (C) 2011 The Combustion Institute. Published by Elsevier Inc. All rights reserved.

Integrated Reservoir Operation Modeling for Irrigation Systems - A Multi-Objective Approach

An integrated reservoir operation model is presented for developing effective operational policies for irrigation water management. In arid and semi-arid climates, owing to dynamic changes in the hydroclimatic conditions within a season, the fixed cropping pattern with conventional operating policies, may have considerable impact on the performance of the irrigation system and may affect the economics of the farming community. For optimal allocation of irrigation water in a season, development of effective mathematical models may guide the water managers in proper decision making and consequently help in reducing the adverse effects of water shortage and crop failure problems. This paper presents a multi-objective integrated reservoir operation model for multi-crop irrigation system. To solve the multi-objective model, a recent swarm intelligence technique, namely elitist-mutated multi-objective particle swarm optimisation (EM-MOPSO) has been used and applied to a case study in India. The method evolves effective strategies for irrigation crop planning and operation policies for a reservoir system, and thereby helps farming community in improving crop benefits and water resource usage in the reservoir command area.

A coupled VOF-IBM-enthalpy approach for modeling motion and growth of equiaxed dendrites in a solidifying melt

A coupled methodology for simulating the simultaneous growth and motion of equiaxed dendrites in solidifying melts is presented. The model uses the volume-averaging principles and combines the features of the enthalpy method for modeling growth, immersed boundary method for handling the rigid solid-liquid interfaces, and the volume of fluid method for tracking the advection of the dendrite. The algorithm also performs explicit-implicit coupling between the techniques used. A two-dimensional framework with incompressible and Newtonian fluid is considered. Validation with available literature is performed and dendrite growth in the presence of rotational and buoyancy driven flow fields is studied. It is seen that the flow fields significantly alter the position and morphology of the dendrites. (C) 2012 Elsevier Inc. All rights reserved.

Modeling Equitable Distribution of Water: Dynamic Inversion-Based Controller Approach

It is a well-known fact that most of the developing countries have intermittent water supply and the quantity of water supplied from the source is also not distributed equitably among the consumers. Aged pipelines, pump failures, and improper management of water resources are some of the main reasons for it. This study presents the application of a nonlinear control technique to overcome this problem in different zones in the city of Bangalore. The water is pumped to the city from a large distance of approximately 100km over a very high elevation of approximately 400m. The city has large undulating terrain among different zones, which leads to unequal distribution of water. The Bangalore, inflow water-distribution system (WDS) has been modeled. A dynamic inversion (DI) nonlinear controller with proportional integral derivative (PID) features (DI-PID) is used for valve throttling to achieve the target flows to different zones of the city. This novel approach of equitable water distribution using DI-PID controllers that can be used as a decision support system is discussed in this paper.

Modeling of dynamic material behavior in hot deformation: Forging of Ti-6242

A new method of modeling material behavior which accounts for the dynamic metallurgical processes occurring during hot deformation is presented. The approach in this method is to consider the workpiece as a dissipator of power in the total processing system and to evaluate the dissipated power co-contentJ = ∫o σ ε ⋅dσ from the constitutive equation relating the strain rate (ε) to the flow stress (σ). The optimum processing conditions of temperature and strain rate are those corresponding to the maximum or peak inJ. It is shown thatJ is related to the strain-rate sensitivity (m) of the material and reaches a maximum value(J max) whenm = 1. The efficiency of the power dissipation(J/J max) through metallurgical processes is shown to be an index of the dynamic behavior of the material and is useful in obtaining a unique combination of temperature and strain rate for processing and also in delineating the regions of internal fracture. In this method of modeling, noa priori knowledge or evaluation of the atomistic mechanisms is required, and the method is effective even when more than one dissipation process occurs, which is particularly advantageous in the hot processing of commercial alloys having complex microstructures. This method has been applied to modeling of the behavior of Ti-6242 during hot forging. The behavior of α+ β andβ preform microstructures has been exam-ined, and the results show that the optimum condition for hot forging of these preforms is obtained at 927 °C (1200 K) and a strain rate of 1CT•3 s•1. Variations in the efficiency of dissipation with temperature and strain rate are correlated with the dynamic microstructural changes occurring in the material.

Modeling growth of hydrogen bubbles in aluminum castings using the level-set method

A new approach is proposed to solve for the growth as well as the movement of hydrogen bubbles during solidification in aluminum castings. A level-set methodology has been adopted to handle this multiphase phenomenon. A microscale domain is considered and the growth and movement of hydrogen bubbles in this domain has been studied. The growth characteristics of hydrogen bubbles have been evaluated under free growth conditions in a melt having a hydrogen input caused b solidification occurring around the microdomain.

State Dependent Attempt Rate Modeling of Single Cell IEEE 802.11 WLANs with Homogeneous Nodes and Poisson Arrivals

Analytical models of IEEE 802.11-based WLANs are invariably based on approximations, such as the well-known mean-field approximations proposed by Bianchi for saturated nodes. In this paper, we provide a new approach for modeling the situation when the nodes are not saturated. We study a State Dependent Attempt Rate (SDAR) approximation to model M queues (one queue per node) served by the CSMA/CA protocol as standardized in the IEEE 802.11 DCF. The approximation is that, when n of the M queues are non-empty, the attempt probability of the n non-empty nodes is given by the long-term attempt probability of n saturated nodes as provided by Bianchi's model. This yields a coupled queue system. When packets arrive to the M queues according to independent Poisson processes, we provide an exact model for the coupled queue system with SDAR service. The main contribution of this paper is to provide an analysis of the coupled queue process by studying a lower dimensional process and by introducing a certain conditional independence approximation. We show that the numerical results obtained from our finite buffer analysis are in excellent agreement with the corresponding results obtained from ns-2 simulations. We replace the CSMA/CA protocol as implemented in the ns-2 simulator with the SDAR service model to show that the SDAR approximation provides an accurate model for the CSMA/CA protocol. We also report the simulation speed-ups thus obtained by our model-based simulation.

Climate change impact assessment: Uncertainty modeling with imprecise probability

Hydrologic impacts of climate change are usually assessed by downscaling the General Circulation Model (GCM) output of large-scale climate variables to local-scale hydrologic variables. Such an assessment is characterized by uncertainty resulting from the ensembles of projections generated with multiple GCMs, which is known as intermodel or GCM uncertainty. Ensemble averaging with the assignment of weights to GCMs based on model evaluation is one of the methods to address such uncertainty and is used in the present study for regional-scale impact assessment. GCM outputs of large-scale climate variables are downscaled to subdivisional-scale monsoon rainfall. Weights are assigned to the GCMs on the basis of model performance and model convergence, which are evaluated with the Cumulative Distribution Functions (CDFs) generated from the downscaled GCM output (for both 20th Century [20C3M] and future scenarios) and observed data. Ensemble averaging approach, with the assignment of weights to GCMs, is characterized by the uncertainty caused by partial ignorance, which stems from nonavailability of the outputs of some of the GCMs for a few scenarios (in Intergovernmental Panel on Climate Change [IPCC] data distribution center for Assessment Report 4 [AR4]). This uncertainty is modeled with imprecise probability, i.e., the probability being represented as an interval gray number. Furthermore, the CDF generated with one GCM is entirely different from that with another and therefore the use of multiple GCMs results in a band of CDFs. Representing this band of CDFs with a single valued weighted mean CDF may be misleading. Such a band of CDFs can only be represented with an envelope that contains all the CDFs generated with a number of GCMs. Imprecise CDF represents such an envelope, which not only contains the CDFs generated with all the available GCMs but also to an extent accounts for the uncertainty resulting from the missing GCM output. This concept of imprecise probability is also validated in the present study. The imprecise CDFs of monsoon rainfall are derived for three 30-year time slices, 2020s, 2050s and 2080s, with A1B, A2 and B1 scenarios. The model is demonstrated with the prediction of monsoon rainfall in Orissa meteorological subdivision, which shows a possible decreasing trend in the future.