Analytical approximation solutions for 3-D optical waveguides: Review

The rectangular dielectric waveguide is the most commonly used structure in integrated optics, especially in semi-conductor diode lasers. Demands for new applications such as high-speed data backplanes in integrated electronics, waveguide filters, optical multiplexers and optical switches are driving technology toward better materials and processing techniques for planar waveguide structures. The infinite slab and circular waveguides that we know are not practical for use on a substrate because the slab waveguide has no lateral confinement and the circular fiber is not compatible with the planar processing technology being used to make planar structures. The rectangular waveguide is the natural structure. In this review, we have discussed several analytical methods for analyzing the mode structure of rectangular structures, beginning with a wave analysis based on the pioneering work of Marcatili. We study three basic techniques with examples to compare their performance levels. These are the analytical approach developed by Marcatili, the perturbation techniques, which improve on the analytical solutions and the effective index method with examples.

Phased-Mission Analysis for Evaluating the Effectiveness of Aerospace Computing-Systems

Effectiveness evaluation of aerospace fault-tolerant computing systems used in a phased-mission environment is rather tricky and difficult because of the interaction of its several degraded performance levels with the multiple objectives of the mission and the use environment. Part I uses an approach based on multiobjective phased-mission analysis to evaluate the effectiveness of a distributed avionics architecture used in a transport aircraft. Part II views the computing system as a multistate s-coherent structure. Lower bounds on the probabilities of accomplishing various levels of performance are evaluated.

Focused Prefetching: Performance Oriented Prefetching Based On Commit Stalls

Loads that miss in L1 or L2 caches and waiting for their data at the head of the ROB cause significant slow down in the form of commit stalls. We identify that most of these commit stalls are caused by a small set of loads, referred to as LIMCOS (Loads Incurring Majority of COmmit Stalls). We propose simple history-based classifiers that track commit stalls suffered by loads to help us identify this small set of loads. We study an application of these classifiers to prefetching. The classifiers are used to train the prefetcher to focus on the misses suffered by LIMCOS. This, referred to as focused prefetching, results in a 9.8% gain in IPC over naive GHB based delta correlation prefetcher along with a 20.3% reduction in memory traffic for a set of 17 memory-intensive SPEC2000 benchmarks. Another important impact of focused prefetching is a 61% improvement in the accuracy of prefetches. We demonstrate that the proposed classification criterion performs better than other existing criteria like criticality and delinquent loads. Also we show that the criterion of focusing on commit stalls is robust enough across cache levels and can be applied to any prefetcher without any modifications to the prefetcher.

Impact of Energy Quantization on the Performance of Current-Biased SET Circuits

The current-biased single electron transistor (SET) (CBS) is an integral part of almost all hybrid CMOS SET circuits. In this paper, for the first time, the effects of energy quantization on the performance of CBS-based circuits are studied through analytical modeling and Monte Carlo simulations. It is demonstrated that energy quantization has no impact on the gain of the CBS characteristics, although it changes the output voltage levels and oscillation periodicity. The effects of energy quantization are further studied for two circuits: negative differential resistance (NDR) and neuron cell, which use the CBS. A new model for the conductance of NDR characteristics is also formulated that includes the energy quantization term.

Effect of residual stresses and metallographic stability on the over all performance of integral diaphragm material

The integral diaphragm pressure transducer consists of a diaphragm machined from precipitation hardened martensitic (APX4) steel. Its performance is quite significant as it depends upon various factors such as mechanical properties including induced residual stress levels, metallurgical and physical parameters due to different stages of processing involved. Hence, the measurement and analysis of residual stress becomes very important from the point of in-service assessment of a component. In the present work, the stress measurements have been done using the X-ray diffraction (XRD) technique, which is a non-destructive test (NDT). This method is more reliable and widely used compared to the other NDT techniques. The metallurgical aspects have been studied by adopting the conventional metallographic practices including examination of microstructure using light microscope. The dimensional measurements have been carried out using dimensional gauge. The results of the present investigation reveals that the diaphragm material after undergoing series of realization processes has yielded good amount of retained austenite in it. Also, the presence of higher compressive stresses induced in the transducer results in non-linearity, zero shift and dimensional instability. The problem of higher retained austenite content and higher compressive stress have been overcome by adopting a new realization process involving machining and cold and hot stabilization soak which has brought down the retained austenite content to about 5–6% and acceptable level of compressive stress in the range −100 to −150 MPa with fine tempered martensitic phase structure and good dimensional stability. The new realization process seems to be quite effective in terms of controlling retained austenite content, residual stress, metallurgical phase as well as dimensional stability and this may result in minimum zero shift of the diaphragm system.

Reservoir performance under uncertainty in hydrologic impacts of climate change

Relatively few studies have addressed water management and adaptation measures in the face of changing water balances due to climate change. The current work studies climate change impact on a multipurpose reservoir performance and derives adaptive policies for possible futurescenarios. The method developed in this work is illustrated with a case study of Hirakud reservoir on the Mahanadi river in Orissa, India,which is a multipurpose reservoir serving flood control, irrigation and power generation. Climate change effects on annual hydropower generation and four performance indices (reliability with respect to three reservoir functions, viz. hydropower, irrigation and flood control, resiliency, vulnerability and deficit ratio with respect to hydropower) are studied. Outputs from three general circulation models (GCMs) for three scenarios each are downscaled to monsoon streamflow in the Mahanadi river for two future time slices, 2045-65 and 2075-95. Increased irrigation demands, rule curves dictated by increased need for flood storage and downscaled projections of streamflow from the ensemble of GCMs and scenarios are used for projecting future hydrologic scenarios. It is seen that hydropower generation and reliability with respect to hydropower and irrigation are likely to show a decrease in future in most scenarios, whereas the deficit ratio and vulnerability are likely to increase as a result of climate change if the standard operating policy (SOP) using current rule curves for flood protection is employed. An optimal monthly operating policy is then derived using stochastic dynamic programming (SDP) as an adaptive policy for mitigating impacts of climate change on reservoir operation. The objective of this policy is to maximize reliabilities with respect to multiple reservoir functions of hydropower, irrigation and flood control. In variations to this adaptive policy, increasingly more weightage is given to the purpose of maximizing reliability with respect to hydropower for two extreme scenarios. It is seen that by marginally sacrificing reliability with respect to irrigation and flood control, hydropower reliability and generation can be increased for future scenarios. This suggests that reservoir rules for flood control may have to be revised in basins where climate change projects an increasing probability of droughts. However, it is also seen that power generation is unable to be restored to current levels, due in part to the large projected increases in irrigation demand. This suggests that future water balance deficits may limit the success of adaptive policy options. (C) 2010 Elsevier Ltd. All rights reserved.

Studies of cryotreatment on the performance of integral diaphragm pressure transducers for space application

The integral diaphragm pressure transducers machined out of precipitation hardened martensite stainless steel (APX4) are widely used for propellant pressure measurements in space applications. These transducers are expected to exhibit dimensional stability and linearity for their entire useful life. These vital factors are very critical for the reliable performance and dependability of the pressure transducers. However, these transducers invariably develop internal stresses during various stages of machining. These stresses have an adverse effect on the performance of the transducers causing deviation from linearity. In order to eliminate these possibilities, it was planned to cryotreat the machined transducers to improve both the long-term linearity and dimensional stability. To study these effects, an experimental cryotreatment unit was designed and developed based on the concept of indirect cooling using the concept of cold nitrogen gas forced closed loop convection currents. The system has the capability of cryotreating large number of samples for varied rates of cooling, soaking and warm-up. After obtaining the initial levels of residual stress and retained austenite using X-ray diffraction techniques, the pressure transducers were cryotreated at 98 K for 36 h. Immediately after cryotreatment, the transducers were tempered at 510 degrees C for 3 h in vacuum furnace. Results after cryo treatment clearly indicated significant reduction in residual stress levels and conversion of retained austenite to martensite. These changes have brought in improvements in long term zero drift and dimensional stability. The cryotreated pressure transducers have been incorporated for actual space applications. (c) 2010 Published by Elsevier Ltd.

Growth and photovoltaic performance of SnS quantum dots

Tin sulphide (SnS) quantum dots of size ranging from 2.4 to 14.4 nm are prepared by chemical precipitation method in aqueous media. Growth of the SnS particles is monitored by controlling the deposition time. Both XRD and SAED patterns confirm that the particles possess orthorhombic structure. The uncapped SnS particles showed secondary phases like Sn2S3 and SnS2 which is visible in the SAED pattern. From the electrochemical characterization. HOMO-LUMO levels of both TiO2 and SnS are determined and the band alignment is found to be favorable for electron transfer from SnS to TiO2. Moreover, the HOMO-LUMO levels varied for different particle sizes. Solar cell is fabricated by sensitizing porous TiO2 thin film with SnS QDs. Cell structure is characterized with and without buffer layer between FTO and TiO2. Without the buffer layer, cell showed an open circuit voltage (V-oc) of 504 mV and short circuit current density (J(sc)) of 2.3 mA/cm(2) under AM1.5 condition. The low fill factor of this structure (15%) is seen to be increased drastically to 51%, on the incorporation of the buffer layer. The cell characteristics are analyzed using two different size quantum dots. (C) 2012 Elsevier B.V. All rights reserved.

Performances of single and two-stage pulse tube cryocoolers under different vacuum levels with and without thermal radiation shields

Single and two-stage Pulse Tube Cryocoolers (PTC) have been designed, fabricated and experimentally studied. The single stage PTC reaches a no-load temperature of similar to 29 K at its cold end, the two-stage PTC reaches similar to 2.9 K in its second stage cold end and similar to 60 K in its first stage cold end. The two-stage Pulse Tube Cryocooler provides a cooling power of similar to 250 mW at 4.2 K. The single stage system uses stainless steel meshes along with Pb granules as its regenerator materials, while the two-stage PTC uses combinations of Pb along with Er3Ni/HoCu2 as the second stage regenerator materials. Normally, the above systems are insulated by thermal radiation shields and mounted inside a vacuum chamber which is maintained at high vacuum. To evaluate the performance of these systems in the possible conditions of loss of vacuum with and without radiation shields, experimental studies have been performed. The heat-in-leak under such severe conditions has been estimated from the heat load characteristics of the respective stages. The experimental results are analyzed to obtain surface emissivities and effective thermal conductivities as a function of interspace pressure.

Prediction of Ground Water Levels in the Uplands of a Tropical Coastal Riparian Wetland using Artificial Neural Networks

Artificial Neural Networks (ANNs) have been found to be a robust tool to model many non-linear hydrological processes. The present study aims at evaluating the performance of ANN in simulating and predicting ground water levels in the uplands of a tropical coastal riparian wetland. The study involves comparison of two network architectures, Feed Forward Neural Network (FFNN) and Recurrent Neural Network (RNN) trained under five algorithms namely Levenberg Marquardt algorithm, Resilient Back propagation algorithm, BFGS Quasi Newton algorithm, Scaled Conjugate Gradient algorithm, and Fletcher Reeves Conjugate Gradient algorithm by simulating the water levels in a well in the study area. The study is analyzed in two cases-one with four inputs to the networks and two with eight inputs to the networks. The two networks-five algorithms in both the cases are compared to determine the best performing combination that could simulate and predict the process satisfactorily. Ad Hoc (Trial and Error) method is followed in optimizing network structure in all cases. On the whole, it is noticed from the results that the Artificial Neural Networks have simulated and predicted the water levels in the well with fair accuracy. This is evident from low values of Normalized Root Mean Square Error and Relative Root Mean Square Error and high values of Nash-Sutcliffe Efficiency Index and Correlation Coefficient (which are taken as the performance measures to calibrate the networks) calculated after the analysis. On comparison of ground water levels predicted with those at the observation well, FFNN trained with Fletcher Reeves Conjugate Gradient algorithm taken four inputs has outperformed all other combinations.

Spatial memory deficits in maternal iron deficiency paradigms are associated with altered glucocorticoid levels

``The goal of this study was to examine the effect of maternal iron deficiency on the developing hippocampus in order to define a developmental window for this effect, and to see whether iron deficiency causes changes in glucocorticoid levels. The study was carried out using pre-natal, post-natal, and pre + post-natal iron deficiency paradigm. Iron deficient pregnant dams and their pups displayed elevated corticosterone which, in turn, differentially affected glucocorticoid receptor (GR) expression in the CA1 and the dentate gyrus. Brain Derived Neurotrophic Factor (BDNF) was reduced in the hippocampi of pups following elevated corticosterone levels. Reduced neurogenesis at P7 was seen in pups born to iron deficient mothers, and these pups had reduced numbers of hippocampal pyramidal and granule cells as adults. Hippocampal subdivision volumes also were altered. The structural and molecular defects in the pups were correlated with radial arm maze performance; reference memory function was especially affected. Pups from dams that were iron deficient throughout pregnancy and lactation displayed the complete spectrum of defects, while pups from dams that were iron deficient only during pregnancy or during lactation displayed subsets of defects. These findings show that maternal iron deficiency is associated with altered levels of corticosterone and GR expression, and with spatial memory deficits in their pups.'' (C) 2013 Elsevier Inc. All rights reserved.

A shortest path tree based algorithm for relay placement in a wireless sensor network and its performance analysis

In this paper, we study a problem of designing a multi-hop wireless network for interconnecting sensors (hereafter called source nodes) to a Base Station (BS), by deploying a minimum number of relay nodes at a subset of given potential locations, while meeting a quality of service (QoS) objective specified as a hop count bound for paths from the sources to the BS. The hop count bound suffices to ensure a certain probability of the data being delivered to the BS within a given maximum delay under a light traffic model. We observe that the problem is NP-Hard. For this problem, we propose a polynomial time approximation algorithm based on iteratively constructing shortest path trees and heuristically pruning away the relay nodes used until the hop count bound is violated. Results show that the algorithm performs efficiently in various randomly generated network scenarios; in over 90% of the tested scenarios, it gave solutions that were either optimal or were worse than optimal by just one relay. We then use random graph techniques to obtain, under a certain stochastic setting, an upper bound on the average case approximation ratio of a class of algorithms (including the proposed algorithm) for this problem as a function of the number of source nodes, and the hop count bound. To the best of our knowledge, the average case analysis is the first of its kind in the relay placement literature. Since the design is based on a light traffic model, we also provide simulation results (using models for the IEEE 802.15.4 physical layer and medium access control) to assess the traffic levels up to which the QoS objectives continue to be met. (C) 2014 Elsevier B.V. All rights reserved.

Influence of dust deposition on photovoltaic panel performance

Solar photovoltaic power plants are ideally located in regions with high insolation levels. Photovoltaic performance is affected by high cell temperatures, soiling, mismatch and other balance-of-systems related losses. It is crucial to understand the significance of each of these losses on system performance. Soiling, highly dependent on installation conditions, is a complex performance issue to accurately quantify. The settlement of dust on panel surfaces may or may not be uniform depending on local terrain and environmental factors such as ambient temperature, wind and rainfall. It is essential to investigate the influence of dust settlement on the operating characteristics of photovoltaic systems to better understand losses in performance attributable to soiling. The current voltage (I-V) characteristics of photovoltaic panels reveal extensive information to support degradation analysis of the panels. This paper attempts to understand performance losses due to dust through a dynamic study into the I-V characteristics of panels under varying soiling conditions in an outdoor experimental test-bed. Further, the results of an indoor study simulating the performance of photovoltaic panels under different dust deposition regimes are discussed in this paper. (C) 2014 Monto Mani. Published by Elsevier Ltd. This is all open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

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.

Performance of WRF-Chem over Indian region: Comparison with measurements

The aerosol mass concentrations over several Indian regions have been simulated using the online chemistry transport model, WRF-Chem, for two distinct seasons of 2011, representing the pre-monsoon (May) and post-monsoon (October) periods during the Indo-US joint experiment `Ganges Valley Aerosol Experiment (GVAX)'. The simulated values were compared with concurrent measurements. It is found that the model systematically underestimates near-surface BC mass concentrations as well as columnar Aerosol Optical Depths (AODs) from the measurements. Examining this in the light of the model-simulated meteorological parameters, we notice the model overestimates both planetary boundary layer height (PBLH) and surface wind speeds, leading to deeper mixing and dispersion and hence lower surface concentrations of aerosols. Shortcoming in simulating rainfall pattern also has an impact through the scavenging effect. It also appears that the columnar AODs are influenced by the unrealistic emission scenarios in the model. Comparison with vertical profiles of BC obtained from aircraft-based measurements also shows a systematic underestimation by the model at all levels. It is seen that concentration of other aerosols, viz., dust and sea-salt are closely linked with meteorological conditions prevailing over the region. Dust is higher during pre-monsoon periods due to the prevalence of north-westerly winds that advect dust from deserts of west Asia into the Indo-Gangetic plain. Winds and rainfall influence sea-salt concentrations. Thus, the unrealistic simulation of wind and rainfall leads to model simulated dust and sea-salt also to deviate from the real values; which together with BC also causes underperformance of the model with regard to columnar AOD. It appears that for better simulations of aerosols over Indian region, the model needs an improvement in the simulation of the meteorology.