Assessing GCM Convergence for India Using the Variable Convergence Score

General circulation models (GCMs) use transient climate simulations to predict climate conditions in the future. Coarse-grid resolutions and process uncertainties necessitate the use of downscaling models to simulate precipitation. However, in the downscaling models, with multiple GCMs now available, selecting an atmospheric variable from a particular model which is representative of the ensemble mean becomes an important consideration. The variable convergence score (VCS) provides a simple yet meaningful approach to address this issue, providing a mechanism to evaluate variables against each other with respect to the stability they exhibit in future climate simulations. In this study, VCS methodology is applied to 10 atmospheric variables of particular interest in downscaling precipitation over India and also on a regional basis. The nested bias-correction methodology is used to remove the systematic biases in the GCMs simulations, and a single VCS curve is developed for the entire country. The generated VCS curve is expected to assist in quantifying the variable performance across different GCMs, thus reducing the uncertainty in climate impact-assessment studies. The results indicate higher consistency across GCMs for pressure and temperature, and lower consistency for precipitation and related variables. Regional assessments, while broadly consistent with the overall results, indicate low convergence in atmospheric attributes for the Northeastern parts of India.

Time-Optimal Convergence to a Rectilinear Path in the Presence of Wind

This paper considers the problem of determining the time-optimal path of a fixed-wing Miniature Air Vehicle (MAV), in the presence of wind. The MAV, which is subject to a bounded turn rate, is required to eventually converge to a straight line starting from a known initial position and orientation. Earlier work in the literature uses Pontryagin's Minimum Principle (PMP) to solve this problem only for the no-wind case. In contrast, the present work uses a geometric approach to solve the problem completely in the presence of wind. In addition, it also shows how PMP can be used to partially solve the problem. Using a 6-DOF model of a MAV the generated optimal path is tracked by an autopilot consisting of proportional-integral-derivative (PID) controllers. The simulation results show the path generation and tracking for cases with steady and time-varying wind. Some issues on real-time path planning are also addressed.

Optimal Trajectory Generation for Convergence to a Rectilinear Path

This paper presents a strategy to determine the shortest path of a fixed-wing Miniature Air Vehicle (MAV), constrained by a bounded turning rate, to eventually fly along a given straight line, starting from an arbitrary but known initial position and orientation. Unlike the work available in the literature that solves the problem using the Pontryagin's Minimum Principle (PMP) the trajectory generation algorithm presented here considers a geometrical approach which is intuitive and easy to understand. This also computes the explicit solution for the length of the optimal path as a function of the initial configuration. Further, using a 6-DOF model of a MAV the generated optimal path is tracked by an autopilot consisting of proportional-integral-derivative (PID) controllers. The simulation results show the path generation and tracking for different cases.

Improving the Sensitivity and Bandwidth of In-Plane Capacitive Microaccelerometers Using Compliant Mechanical Amplifiers

This paper presents a method to enhance both the sensitivity and bandwidth of in-plane capacitive micromachined accelerometers by using compliant mechanical amplifiers, and thus obviating the compromise between the sensitivity and bandwidth. Here, we compare one of the most sensitive single-axis capacitive accelerometers and another with large resonant frequency reported in the literature with the modified designs that include displacement-amplifying compliant mechanisms (DaCMs) occupying the same footprint and under identical conditions. We show that 62% improvement in sensitivity and 34% improvement in bandwidth in the former, and 27% and 25% in the latter can be achieved. Also presented here is a dual-axis accelerometer that uses a suspension that decouples and amplifies the displacements along the two in-plane orthogonal axes. The new design was microfabricated, packaged, and tested. The device is 25-mu m thick with the interfinger gap as large as 4 m. Despite the simplicity of the microfabrication process, the measured axial sensitivity (static) of about 0.58 V/g for both the axes was achieved with a cross-axis sensitivity of less than +/- 2%. The measured natural frequency along the two in-plane axes was 920 Hz. Displacement amplification of 6.2 was obtained using the DaCMs in the dual-axis accelerometer. 2013-0083]

Narrow band gap conjugated polymer for improving the photovoltaic performance of P3HT:PCBM ternary blend bulk heterojunction solar cells

A new D-A structured conjugated polymer (PBDO-T-TDP) based on electron-rich benzo 1,2-b:4,5-b'] difuran (BDO) containing conjugated alkylthiophene side chains with an electron-deficient diketopyrrolopyrrole (DPP) derivative is designed and synthesized. The polymer shows a narrow band gap with broad UV-Visible absorption spectra, which is in contrast to that of the P3HT:PCBM binary blend. Furthermore, its energy levels can meet the energetic requirement of the cascaded energy levels of P3HT and PCBM. Therefore, PBDO-T-TDP is used as a sensitizer in P3HT: PCBM based BHJ solar cells and its effect on their photovoltaic properties was investigated by blending them together at various weight ratios. It is observed that the resulting ternary blend system exhibited a significant improvement in the device performance (similar to 3.10%) as compared with their binary ones (similar to 2.15%). Such an enhancement in the ternary blend system is ascribed to their balanced hole and electron mobility along with uniform distribution of PBDO-T-TDP in the blend system, as revealed by organic field effect transistors and AFM studies.

Adaptive Mesh Refinement for Fast Convergence of EFIE-Based 3-D Extraction

3-D full-wave method of moments (MoM) based electromagnetic analysis is a popular means toward accurate solution of Maxwell's equations. The time and memory bottlenecks associated with such a solution have been addressed over the last two decades by linear complexity fast solver algorithms. However, the accurate solution of 3-D full-wave MoM on an arbitrary mesh of a package-board structure does not guarantee accuracy, since the discretization may not be fine enough to capture spatial changes in the solution variable. At the same time, uniform over-meshing on the entire structure generates a large number of solution variables and therefore requires an unnecessarily large matrix solution. In this paper, different refinement criteria are studied in an adaptive mesh refinement platform. Consequently, the most suitable conductor mesh refinement criterion for MoM-based electromagnetic package-board extraction is identified and the advantages of this adaptive strategy are demonstrated from both accuracy and speed perspectives. The results are also compared with those of the recently reported integral equation-based h-refinement strategy. Finally, a new methodology to expedite each adaptive refinement pass is proposed.

Descending from infinity: Convergence of tailed distributions

We investigate the relaxation of long-tailed distributions under stochastic dynamics that do not support such tails. Linear relaxation is found to be a borderline case in which long tails are exponentially suppressed in time but not eliminated. Relaxation stronger than linear suppresses long tails immediately, but may lead to strong transient peaks in the probability distribution. We also find that a delta-function initial distribution under stronger than linear decay displays not one but two different regimes of diffusive spreading.

A Multi-phase Approach for Improving Information Diffusion in Social Networks

For maximizing influence spread in a social network, given a certain budget on the number of seed nodes, we investigate the effects of selecting and activating the seed nodes in multiple phases. In particular, we formulate an appropriate objective function for two-phase influence maximization under the independent cascade model, investigate its properties, and propose algorithms for determining the seed nodes in the two phases. We also study the problem of determining an optimal budget-split and delay between the two phases.

Modified Greedy Pursuits for Improving Sparse Recovery

Compressive Sensing (CS) theory combines the signal sampling and compression for sparse signals resulting in reduction in sampling rate. In recent years, many recovery algorithms have been proposed to reconstruct the signal efficiently. Subspace Pursuit and Compressive Sampling Matching Pursuit are some of the popular greedy methods. Also, Fusion of Algorithms for Compressed Sensing is a recently proposed method where several CS reconstruction algorithms participate and the final estimate of the underlying sparse signal is determined by fusing the estimates obtained from the participating algorithms. All these methods involve solving a least squares problem which may be ill-conditioned, especially in the low dimension measurement regime. In this paper, we propose a step prior to least squares to ensure the well-conditioning of the least squares problem. Using Monte Carlo simulations, we show that in low dimension measurement scenario, this modification improves the reconstruction capability of the algorithm in clean as well as noisy measurement cases.

Improving the Rigor and Consistency of the Thermodynamic Theory for Clathrate Hydrates through Incorporation of Movement of Water Molecules of Hydrate Lattice

Current applications of statistical thermodynamic theories for clathrate hydrates do not incorporate the translational and rotational movement of water molecules of the hydrate lattice,in a rigorous manner. Previous studies have shown that the movement of water molecules has a significant effect on the properties of clathrate hydrates. In this Article, a method is presented to incorporate the effect of water movement with as much rigor as possible. This method is then used to calculate the Langmuir constant of the guest species in a clathrate hydrate. Unlike previous studies on modeling of clathrate hydrate thermodynamics, the method presented in this paper does not regress either the intermolecular potentials or the properties of the empty hydrate from clathrate phase equilibria data. Also the properties of empty hydrate used in the theory do not depend on the nature and composition of the guest molecules. The predicted phase equilibria from the resulting theory are shown to be highly accurate and thermodynamically consistent by comparing them with the phase equilibria computed directly from molecular simulations.

GROUND COOLING SYSTEM FOR IMPROVING THE EFFICIENCY OF LOW TEMPERATURE POWER GENERATION

This paper presents an analysis of an organic Rankine cycle (ORC) with dry cooling system aided by an earth-coupled passive cooling system. Several organic fluids were considered as working fluids in the ORC in the temperature range of 125-200 degrees C. An earth-air-heat-exchanger (EMU) is studied for a location in the United States (Las Vegas) and another in India (New Delhi), to pre cool the ambient air before entering an air-cooled condenser (ACC). It was observed that the efficiency of the system improved by 1-3% for the system located in Las Vegas and fluctuations associated with temperature variations of the ambient air were also reduced when the EAHE system was used. A ground-coupled heat pump (GCHP) is also studied for these locations where cooling water is pre cooled in an underground buried pipe before entering a condenser heat exchanger in a closed loop. The area of the buried pipe and the condenser size are calculated per kW of power generation for various working fluids.

Bi-Modal DRAM Cache: Improving Hit Rate, Hit Latency and Bandwidth

In this paper, we present Bi-Modal Cache - a flexible stacked DRAM cache organization which simultaneously achieves several objectives: (i) improved cache hit ratio, (ii) moving the tag storage overhead to DRAM, (iii) lower cache hit latency than tags-in-SRAM, and (iv) reduction in off-chip bandwidth wastage. The Bi-Modal Cache addresses the miss rate versus off-chip bandwidth dilemma by organizing the data in a bi-modal fashion - blocks with high spatial locality are organized as large blocks and those with little spatial locality as small blocks. By adaptively selecting the right granularity of storage for individual blocks at run-time, the proposed DRAM cache organization is able to make judicious use of the available DRAM cache capacity as well as reduce the off-chip memory bandwidth consumption. The Bi-Modal Cache improves cache hit latency despite moving the metadata to DRAM by means of a small SRAM based Way Locator. Further by leveraging the tremendous internal bandwidth and capacity that stacked DRAM organizations provide, the Bi-Modal Cache enables efficient concurrent accesses to tags and data to reduce hit time. Through detailed simulations, we demonstrate that the Bi-Modal Cache achieves overall performance improvement (in terms of Average Normalized Turnaround Time (ANTT)) of 10.8%, 13.8% and 14.0% in 4-core, 8-core and 16-core workloads respectively.

Learning-Based Fast Iterative Convergence of 3-D MoM via Eigen-AGMRES Method

Three-dimensional (3-D) full-wave electromagnetic simulation using method of moments (MoM) under the framework of fast solver algorithms like fast multipole method (FMM) is often bottlenecked by the speed of convergence of the Krylov-subspace-based iterative process. This is primarily because the electric field integral equation (EFIE) matrix, even with cutting-edge preconditioning techniques, often exhibits bad spectral properties arising from frequency or geometry-based ill-conditioning, which render iterative solvers slow to converge or stagnate occasionally. In this communication, a novel technique to expedite the convergence of MoMmatrix solution at a specific frequency is proposed, by extracting and applying Eigen-vectors from a previously solved neighboring frequency in an augmented generalized minimum residual (AGMRES) iterative framework. This technique can be applied in unison with any preconditioner. Numerical results demonstrate up to 40% speed-up in convergence using the proposed Eigen-AGMRES method.

Nickel Electrode for Improving Current Density in Organic Electronic Device

In this work, polymer diode performance was analyzed by using nickel as anode electrode from two kinds of nickel as starting materials, namely nickel wire Ni{B} and nickel nano-particle Ni{N}. Metal electrode surface roughness and grain morphology were investigated by atomic force microscope and scanning electron microscope, respectively. Current-voltage (I-V) and capacitance-voltage (C-V) characteristics were measured for the fabricated device at room temperature. Obtained result from the current-voltage characteristics shows an increment in the current density for nickel nano-particle top electrode device. The increase in the current density could be due to a reduction in built-in voltage at P3HT/Ni{N} interface.

Analysis of Factors for Improving Functionality of Tin Oxide Gas Sensor

The proposed work discusses different parameters which are considered to improve the performance of a tin oxide-based thin film gas sensor. This includes analysing and deducing suitable catalytic additives to enhance the performance of the sensor in terms of selectivity and sensitivity. Chemical sensitization and electronic sensitization are performed to improve the rate of response of the sensor.