Expanding universe: thermodynamical aspects from different models

The pivotal point of the paper is to discuss the behavior of temperature, pressure, energy density as a function of volume along with determination of caloric EoS from following two model: w(z)=w (0)+w (1)ln(1+z) & . The time scale of instability for this two models is discussed. In the paper we then generalize our result and arrive at general expression for energy density irrespective of the model. The thermodynamical stability for both of the model and the general case is discussed from this viewpoint. We also arrive at a condition on the limiting behavior of thermodynamic parameter to validate the third law of thermodynamics and interpret the general mathematical expression of integration constant U (0) (what we get while integrating energy conservation equation) physically relating it to number of micro states. The constraint on the allowed values of the parameters of the models is discussed which ascertains stability of universe. The validity of thermodynamical laws within apparent and event horizon is discussed.

High-temperature kinetics of the reaction between CN and hydrocarbons using a novel high-enthalpy flow tube

More than 70 molecules of varied nature have been identified in the envelopes of carbon-rich stars through their spectral fingerprints in the microwave or far infrared regions. Many of them are carbon chain molecules and radicals, and a significant number are unique to the circumstellar medium. The determination of relevant laboratory kinetics data is critical to keep up with the development of the high spectral and spatial resolution observations and of the refinement of chemical models. Neutralneutral reactions of the CN radical with unsaturated hydrocarbons could be a dominant route in the formation of cyanopolyynes, even at low temperatures and deserve a detailed laboratory investigation. The approach we have developed aims to bridge the temperature gap between resistively heated flow tubes and shock tubes. The present kinetic measurements are obtained using a new reactor combining a high-enthalpy source with a flow tube and a pulsed laser photolysislaser-induced fluorescence system to probe the undergoing chemical reactions. The high-enthalpy flow tube has been used to measure the rate constant of the reaction of the CN radical with propane (C3H8), propene (C3H6), allene (C3H4), 1,3-butadiene (1,3-C4H6), and 1-butyne (C4H6) over a temperature range extending from 300 to 1200 K. All studied reactions of CN with unsaturated hydrocarbons are rapid, with rate coefficients greater than 10-10 cm3 center dot molecule-1 center dot s-1 and exhibit slight negative temperature dependence above room temperature. (c) 2012 Wiley Periodicals, Inc. Int J Chem Kinet 44: 753766, 2012

Synthesis of free standing nanocrystalline Cu by ball milling at cryogenic temperature

This paper reports for the first time synthesis of free standing nano-crystalline copper crystals of a similar to 30-40 nm by ball milling of copper powder at 150 K under Argon atmosphere in a specially designed cryomill. The detailed characterization of these particles using multiple techniques that includes transmission electron microscopy confirms our conclusion. Careful analysis of the chemistry of these particles indicates that these particles are essentially contamination free. Through the analysis of existing models of grain size refinements during ball milling and low temperature deformation, we argue that the suppression of thermal processes and low temperature leads to formation of free nanoparticles as the process of fracture dominates over possible cold welding at low temperatures. (C) 2012 Elsevier B.V. All rights reserved.

High-temperature, high-pressure granulites (retrogressed eclogites) in the central region of the Lewisian, NW Scotland: Crustal-scale subduction in the Neoarchaean

Eclogites and associated high-pressure (HP) rocks in collisional and accretionary orogenic belts preserve a record of subduction and exhumation, and provide a key constraint on the tectonic evolution of the continents. Most eclogites that formed at high pressures but low temperatures at > 10-11 kbar and 450-650 degrees C can be interpreted as a result of subduction of cold oceanic lithosphere. A new class of high-temperature (HT) eclogites that formed above 900 degrees C and at 14 to 30 kbar occurs in the deep continental crust, but their geodynamic significance and processes of formation are poorly understood. Here we show that Neoarchaean mafic-ultramafic complexes in the central granulite facies region of the Lewisian in NW Scotland contain HP/HT garnet-bearing granulites (retrogressed eclogites), gabbros, Iherzolites, and websterites, and that the HP granulites have garnets that contain inclusions of omphacite. From thermodynamic modeling and compositional isopleths we calculate that peak eclogite-facies metamorphism took place at 24-22 kbar and 1060-1040 degrees C. The geochemical signature of one (G-21) of the samples shows a strong depletion of Eu indicating magma fractionation at a crustal level. The Sm-Nd isochron ages of HP phases record different cooling ages of ca. 2480 and 2330 Ma. We suggest that the layered mafic-ultramafic complexes, which may have formed in an oceanic environment, were subducted to eclogite depths, and exhumed as HP garnet-bearing orogenic peridotites. The layered complexes were engulfed by widespread orthogneisses of tonalite-trondhjemite-granodiorite (TTG) composition with granulite facies assemblages. We propose two possible tectonic models: (1) the fact that the relicts of eclogitic complexes are so widespread in the Scourian can be taken as evidence that a >90 km x 40 km-size slab of continental crust containing mafic-ultramafic complexes was subducted to at least 70 km depth in the late Archaean. During exhumation the gneiss protoliths were retrogressed to granulite facies assemblages, but the mafic-ultramafic rocks resisted retrogression. (2) The layered complexes of mafic and ultramafic rocks were subducted to eclogite-facies depths and during exhumation under crustal conditions they were intruded by the orthogneiss protoliths (TTG) that were metamorphosed in the granulite facies. Apart from poorly defined UHP metamorphic rocks in Norway, the retrogressed eclogites in the central granulite/retrogressed eclogite facies Lewisian region, NW Scotland have the highest crustal pressures so far reported for Archaean rocks, and demonstrate that lithospheric subduction was transporting crustal rocks to HP depths in the Neoarchaean. (C) 2012 International Association for Gondwana Research. Published by Elsevier B.V. All rights reserved.

Experimental determination and activity coefficient based models for mixture solubilities of nitrophenol isomers in supercritical carbon dioxide

The experimental solubilities of the mixture of nitrophenol (m- and p-) isomers were determined at 308, 318 and 328 K over a pressure range of 10-17.55 MPa. Compared to the binary solubilities, the ternary solubilities of m-nitrophenol increased at 308, 318 and 328 K. The ternary solubilities of p-nitrophenol increased at 308 K, while the ternary solubilities decreased at lower pressures and increased at higher pressure at 318 and 328 K. The solubilities of the solid mixtures in supercritical carbon dioxide (SCCO2) were correlated with solution models by incorporating the non-idealities using activity coefficient based models. The Wilson and NRTL activity coefficient models were applied to determine the nature of the interactions between the molecules. The equation developed by using the NRTL model has three parameters and correlates mixture solubilities of solid solutes in terms of temperature and cosolute composition. The equation derived from the Wilson model contains five parameters and correlates solubilities in terms of temperature, density and cosolute composition. These two new equations developed in this work were used to correlate the solubilities of 25 binary solid mixtures including the current data. The average AARDs of the model equations derived using the NRTL and Wilson models for the solid mixtures were found to be 7% and 4%, respectively. (C) 2012 Elsevier B.V. All rights reserved.

Experimental analysis of composite single-lap joints using digital image correlation and comparison with theoretical models

The demand for energy efficient, low weight structures has boosted the use of composite structures assembled using increased quantities of structural adhesives. Bonded structures may be subjected to severe working environments such as high temperature and moisture due to which the adhesive gets degraded over a period of time. This reduces the strength of a joint and leads to premature failure. Measurement of strains in the adhesive bondline at any point of time during service may be beneficial as an assessment can be made on the integrity of a joint and necessary preventive actions may be taken before failure. This paper presents an experimental approach of measuring peel and shear strains in the adhesive bondline of composite single-lap joints using digital image correlation. Different sets of composite adhesive joints with varied bond quality were prepared and subjected to tensile load during which digital images were taken and processed using digital image correlation software. The measured peel strain at the joint edge showed a rapid increase with the initiation of a crack till failure of the joint. The measured strains were used to compute the corresponding stresses assuming a plane strain condition and the results were compared with stresses predicted using theoretical models, namely linear and nonlinear adhesive beam models. A similar trend in stress distribution was observed. Further comparison of peel and shear strains also exhibited similar trend for both healthy and degraded joints. Maximum peel stress failure criterion was used to predict the failure load of a composite adhesive joint and a comparison was made between predicted and actual failure loads. The predicted failure loads from theoretical models were found to be higher than the actual failure load for all the joints.

A simple model for spatial disaggregation of evaporative fraction: Comparative study with thermal sharpened land surface temperature data over India

[1] Evaporative fraction (EF) is a measure of the amount of available energy at the earth surface that is partitioned into latent heat flux. The currently operational thermal sensors like the Moderate Resolution Imaging Spectroradiometer (MODIS) on satellite platforms provide data only at 1000 m, which constraints the spatial resolution of EF estimates. A simple model (disaggregation of evaporative fraction (DEFrac)) based on the observed relationship between EF and the normalized difference vegetation index is proposed to spatially disaggregate EF. The DEFrac model was tested with EF estimated from the triangle method using 113 clear sky data sets from the MODIS sensor aboard Terra and Aqua satellites. Validation was done using the data at four micrometeorological tower sites across varied agro-climatic zones possessing different land cover conditions in India using Bowen ratio energy balance method. The root-mean-square error (RMSE) of EF estimated at 1000 m resolution using the triangle method was 0.09 for all the four sites put together. The RMSE of DEFrac disaggregated EF was 0.09 for 250 m resolution. Two models of input disaggregation were also tried with thermal data sharpened using two thermal sharpening models DisTrad and TsHARP. The RMSE of disaggregated EF was 0.14 for both the input disaggregation models for 250 m resolution. Moreover, spatial analysis of disaggregation was performed using Landsat-7 (Enhanced Thematic Mapper) ETM+ data over four grids in India for contrasted seasons. It was observed that the DEFrac model performed better than the input disaggregation models under cropped conditions while they were marginally similar under non-cropped conditions.

Copula-Based Modeling of TMI Brightness Temperature With Rainfall Type

Overland rain retrieval using spaceborne microwave radiometer offers a myriad of complications as land presents itself as a radiometrically warm and highly variable background. Hence, land rainfall algorithms of the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) have traditionally incorporated empirical relations of microwave brightness temperature (Tb) with rain rate, rather than relying on physically based radiative transfer modeling of rainfall (as implemented in the TMI ocean algorithm). In this paper, sensitivity analysis is conducted using the Spearman rank correlation coefficient as benchmark, to estimate the best combination of TMI low-frequency channels that are highly sensitive to the near surface rainfall rate from the TRMM Precipitation Radar (PR). Results indicate that the TMI channel combinations not only contain information about rainfall wherein liquid water drops are the dominant hydrometeors but also aid in surface noise reduction over a predominantly vegetative land surface background. Furthermore, the variations of rainfall signature in these channel combinations are not understood properly due to their inherent uncertainties and highly nonlinear relationship with rainfall. Copula theory is a powerful tool to characterize the dependence between complex hydrological variables as well as aid in uncertainty modeling by ensemble generation. Hence, this paper proposes a regional model using Archimedean copulas, to study the dependence of TMI channel combinations with respect to precipitation, over the land regions of Mahanadi basin, India, using version 7 orbital data from the passive and active sensors on board TRMM, namely, TMI and PR. Studies conducted for different rainfall regimes over the study area show the suitability of Clayton and Gumbel copulas for modeling convective and stratiform rainfall types for the majority of the intraseasonal months. Furthermore, large ensembles of TMI Tb (from the most sensitive TMI channel combination) were generated conditional on various quantiles (25th, 50th, 75th, and 95th) of the convective and the stratiform rainfall. Comparatively greater ambiguity was observed to model extreme values of the convective rain type. Finally, the efficiency of the proposed model was tested by comparing the results with traditionally employed linear and quadratic models. Results reveal the superior performance of the proposed copula-based technique.

Multi-site downscaling of maximum and minimum daily temperature using support vector machine

Climate change impact assessment studies involve downscaling large-scale atmospheric predictor variables (LSAPVs) simulated by general circulation models (GCMs) to site-scale meteorological variables. This article presents a least-square support vector machine (LS-SVM)-based methodology for multi-site downscaling of maximum and minimum daily temperature series. The methodology involves (1) delineation of sites in the study area into clusters based on correlation structure of predictands, (2) downscaling LSAPVs to monthly time series of predictands at a representative site identified in each of the clusters, (3) translation of the downscaled information in each cluster from the representative site to that at other sites using LS-SVM inter-site regression relationships, and (4) disaggregation of the information at each site from monthly to daily time scale using k-nearest neighbour disaggregation methodology. Effectiveness of the methodology is demonstrated by application to data pertaining to four sites in the catchment of Beas river basin, India. Simulations of Canadian coupled global climate model (CGCM3.1/T63) for four IPCC SRES scenarios namely A1B, A2, B1 and COMMIT were downscaled to future projections of the predictands in the study area. Comparison of results with those based on recently proposed multivariate multiple linear regression (MMLR) based downscaling method and multi-site multivariate statistical downscaling (MMSD) method indicate that the proposed method is promising and it can be considered as a feasible choice in statistical downscaling studies. The performance of the method in downscaling daily minimum temperature was found to be better when compared with that in downscaling daily maximum temperature. Results indicate an increase in annual average maximum and minimum temperatures at all the sites for A1B, A2 and B1 scenarios. The projected increment is high for A2 scenario, and it is followed by that for A1B, B1 and COMMIT scenarios. Projections, in general, indicated an increase in mean monthly maximum and minimum temperatures during January to February and October to December.

Development and Evaluation of Statistical Downscaling Models for Monthly Precipitation

Several statistical downscaling models have been developed in the past couple of decades to assess the hydrologic impacts of climate change by projecting the station-scale hydrological variables from large-scale atmospheric variables simulated by general circulation models (GCMs). This paper presents and compares different statistical downscaling models that use multiple linear regression (MLR), positive coefficient regression (PCR), stepwise regression (SR), and support vector machine (SVM) techniques for estimating monthly rainfall amounts in the state of Florida. Mean sea level pressure, air temperature, geopotential height, specific humidity, U wind, and V wind are used as the explanatory variables/predictors in the downscaling models. Data for these variables are obtained from the National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP-NCAR) reanalysis dataset and the Canadian Centre for Climate Modelling and Analysis (CCCma) Coupled Global Climate Model, version 3 (CGCM3) GCM simulations. The principal component analysis (PCA) and fuzzy c-means clustering method (FCM) are used as part of downscaling model to reduce the dimensionality of the dataset and identify the clusters in the data, respectively. Evaluation of the performances of the models using different error and statistical measures indicates that the SVM-based model performed better than all the other models in reproducing most monthly rainfall statistics at 18 sites. Output from the third-generation CGCM3 GCM for the A1B scenario was used for future projections. For the projection period 2001-10, MLR was used to relate variables at the GCM and NCEP grid scales. Use of MLR in linking the predictor variables at the GCM and NCEP grid scales yielded better reproduction of monthly rainfall statistics at most of the stations (12 out of 18) compared to those by spatial interpolation technique used in earlier studies.

Room-temperature bandlike transport and Hall effect in a high-mobility ambipolar polymer

The advent of a new class of high-mobility semiconducting polymers opens up a window to address fundamental issues in electrical transport mechanism such as transport between localized states versus extended state conduction. Here, we investigate the origin of the ultralow degree of disorder (E-a similar to 16 meV) and the ``bandlike'' negative temperature (T) coefficient of the field effect electron mobility: mu(e)(FET) (T) in a high performance (mu(e)(FET) > 2.5 cm(2) V-1 s(-1)) diketopyrrolopyrrole based semiconducting polymer. Models based on the framework of mobility edge with exponential density of states are invoked to explain the trends in transport. The temperature window over which the system demonstrates delocalized transport was tuned by a systematic introduction of disorder at the transport interface. Additionally, the Hall mobility (mu(e)(Hall)) extracted from Hall voltage measurements in these devices was found to be comparable to field effect mobility (mu(e)(FET)) in the high T bandlike regime. Comprehensive studies with different combinations of dielectrics and semiconductors demonstrate the effectiveness of rationale molecular design, which emphasizes uniform-energetic landscape and low reorganization energy.

Prediction of Land Surface Temperature under Cloudy Conditions using Microwave Remote Sensing and ANN

Land surface temperature (LST) is an important variable in climate, hydrologic, ecological, biophysical and biochemical studies (Mildrexler et al., 2011). The most effective way to obtain LST measurements is through satellites. Presently, LST from moderate resolution imaging spectroradiometer (MODIS) sensor is applied in various fields due to its high spatial and temporal availability over the globe, but quite difficult to provide observations in cloudy conditions. This study evolves of prediction of LST under clear and cloudy conditions using microwave vegetation indices (MVIs), elevation, latitude, longitude and Julian day as inputs employing an artificial neural network (ANN) model. MVIs can be obtained even under cloudy condition, since microwave radiation has an ability to penetrate through clouds. In this study LST and MVIs data of the year 2010 for the Cauvery basin on a daily basis were obtained from MODIS and advanced microwave scanning radiometer (AMSR-E) sensors of aqua satellite respectively. Separate ANN models were trained and tested for the grid cells for which both LST and MVI were available. The performance of the models was evaluated based on standard evaluation measures. The best performing model was used to predict LST where MVIs were available. Results revealed that predictions of LST using ANN are in good agreement with the observed values. The ANN approach presented in this study promises to be useful for predicting LST using satellite observations even in cloudy conditions. (C) 2015 The Authors. Published by Elsevier B.V.

Ranking general circulation models for India using TOPSIS

Eleven general circulation models/global climate models (GCMs) - BCCR-BCCM2.0, INGV-ECHAM4, GFDL2.0, GFDL2.1, GISS, IPSL-CM4, MIROC3, MRI-CGCM2, NCAR-PCMI, UKMO-HADCM3 and UKMO-HADGEM1 - are evaluated for Indian climate conditions using the performance indicator, skill score (SS). Two climate variables, temperature T (at three levels, i.e. 500, 700, 850 mb) and precipitation rate (Pr) are considered resulting in four SS-based evaluation criteria (T500, T700, T850, Pr). The multicriterion decision-making method, technique for order preference by similarity to an ideal solution, is applied to rank 11 GCMs. Efforts are made to rank GCMs for the Upper Malaprabha catchment and two river basins, namely, Krishna and Mahanadi (covered by 17 and 15 grids of size 2.5 degrees x 2.5 degrees, respectively). Similar efforts are also made for India (covered by 73 grid points of size 2.5 degrees x 2.5 degrees) for which an ensemble of GFDL2.0, INGV-ECHAM4, UKMO-HADCM3, MIROC3, BCCR-BCCM2.0 and GFDL2.1 is found to be suitable. It is concluded that the proposed methodology can be applied to similar situations with ease.

Generation of Temperature Dependent Transversely Isotropic Properties for Zigzag and Armchair Single-Walled Carbon Nanotubes

Finite element analysis has been carried out to obtain temperature dependent transversely isotropic properties of the single-walled carbon nanotubes (SWCNTs). Finite element models of SWCNTs are generated by specifying the C-C bond rigidities. The five independent transversely isotropic properties for different chiralities are evaluated using the stress fields of thick-walled cylinders and the elastic deformations of SWCNTs subjected to pure extension, internal pressure and pure torsion loads. Empirical relations are provided for the five independent elastic constants useful to armchair and zigzag SWCNTs.

Experimental solubilities of two lipid derivatives in supercritical carbon dioxide and new correlations based on activity coefficient models

The solubilities of two lipid derivatives, geranyl butyrate and 10-undecen-1-ol, in SCCO2 (supercritical carbon dioxide) were measured at different operating conditions of temperature (308.15 to 333.15 K) and pressure (10 to 18 MPa). The solubilities (in mole fraction) ranged from 2.1 x 10(-3) to 23.2 x 10(-3) for geranyl butyrate and 2.2 x 10(-3) to 25.0 x 10(-3) for 10-undecen-1-ol, respectively. The solubility data showed a retrograde behavior in the pressure and temperature range investigated. Various combinations of association and solution theory along with different activity coefficient models were developed. The experimental data for the solubilities of 21 liquid solutes along with geranyl butyrate and 10-undecen-1-ol were correlated using both the newly derived models and the existing models. The average deviation of the correlation of the new models was below 15%.