A novel technique for direct reuse of wastewater in combining scouring and bleaching of cotton fabric

Abstract

Wastewater generated from the conventional pretreatment process is having potential to reuse several times for pretreatment of subsequent batches without harming the fabric quality. As the major portion of water is used in textile pretreatment processes, in the present work a novel method was studied for direct reuse of wastewater in combining scouring and bleaching process. The wastewater generated by the conventional pretreatment was reused with and without mixing with freshwater. Simple technique like filtration with nylon mesh was also studied for its effects on efficiency of pretreatment. The pretreated fabrics were characterized using advanced techniques and further evaluated towards efficiency of scouring and bleaching. In order to evaluate the effect of novel pretreatment process involving reuse of wastewater on dyeability, the pretreated fabrics (using both conventional and novel methods) were further studied for dyeability using reactive dyes. The resulting wastewaters were characterized before reuse in novel method. The pretreated fabrics showed insignificant variations in strength and pretreatment efficiency. The dyeability of both fabrics towards reactive dyes was comparable. The volume of effluent generated was greatly reduced in novel method which showed a great promise to save 33% of water in pretreatment process of cotton fabric.     

A robust µopt‐LMS algorithm for the tracking of fading channels

This paper presents an application of LMS algorithm with optimum step size (µ_opt‐LMS) for fading channel estimation. The expression for optimum step size of the LMS algorithm is modified for use in the fading channel estimation problem. The robustness of the proposed µ_opt‐LMS algorithm is demonstrated via simulation in different channel conditions. Copyright © 2002 John Wiley & Sons, Ltd.     

A comparative study of the tool–chip contact length in turning of two engineering alloys for a wide range of cutting speeds

Tool chip contact length is an important parameter in machining, as it provides an indication of the size of area of interaction between the hot chip and the tool surface and hence the interface heat transfer zone. Heat transfer and thermally activated wear modes usually dominate tool wear in the high speed machining of steels and machining of titanium alloys at most cutting speeds. In this study, existing models for the prediction of tool–chip contact length are reviewed and examined for their suitability in high speed machining of two widely used engineering alloys. Orthogonal turning tests for AISI 1045 steel and Ti6Al4V titanium alloy are conducted for a range of cutting speeds from conventional to high speeds. New contact length models are presented for both materials covering a wide range of cutting speeds. More significantly, these contact length models are appropriate for high speed machining where thermal loads significantly influence process performance. Additionally, the work discusses how the machinability of engineering materials influences the ability to predict contact length.     

Cellular DNA breakage by soy isoflavone genistein and its methylated structural analogue biochanin A

Epidemiological studies have indicated that populations with high isoflavone intake through soy consumption have lower rates of breast, prostate, and colon cancer. The isoflavone polyphenol genistein in soybean is considered to be a potent chemopreventive agent against cancer. In order to explore the chemical basis of chemopreventive activity of genistein, in this paper we have examined the structure–activity relationship between genistein and its structural analogue biochanin A. We show that both genistein and its methylated derivative biochanin A are able to mobilize nuclear copper in human lymphocyte, leading to degradation of cellular DNA. However, the relative rate of DNA breakage was greater in the case of genistein. Further, the cellular DNA degradation was inhibited by copper chelator (neocuproine/bathocuproine) but not by compounds that specifically bind iron and zinc (desferrioxamine mesylate and histidine, respectively). We also compared the antioxidant activity of the two isoflavones against tert‐butylhydroperoxide‐induced oxidative breakage in lymphocytes. Again genistein was found to be more effective than biochanin A in providing protection against oxidative stress induced by tert‐butylhydroperoxide. It would therefore appear that the structural features of isoflavones that are important for antioxidant properties are also the ones that contribute to their pro‐oxidant action through a mechanism that involves redox cycling of chromatin‐bound nuclear copper.     

Application of neural networks to predict the steady state performance of a Run-Around Membrane Energy Exchanger

Modeling the performance characteristics of thermal systems has been a research interest for many decades with moisture transfer systems experiencing a resurgence over the last decade, especially in heating, ventilating, and air conditioning (HVAC) applications. In this study, a neural network (NN) model is developed to predict the heat and moisture transfer performances (i.e., the sensible and latent effectivenesses) of a novel HVAC energy exchanger called the Run-Around Membrane Energy Exchanger (RAMEE) which is able to transfer both heat and moisture between exhaust and supply air streams. The training data set for the NN model covers a wide range of design and operating parameters and is produced using an experimentally validated finite difference (FD) model. Two separate NNs (one for sensible and one for latent energy transfer) each with five inputs and one output, are selected to represent the RAMEE. The results from NN models are numerically and experimentally validated. The root mean squared error (RMSE) between the FD and NN models are 0.05 °C and 2 × 10^?5 kg_v/kg_a, indicating satisfactory agreement for energy exchange calculations. The paper reports the weights and biases to make the results of this study reproducible. These NN models are very fast and easy to use therefore, they might be used for design and for estimating the annual energy savings in different buildings which use the RAMEE in their HVAC system. Additionally, the NN models can be used with optimization algorithms to maximize energy savings and minimize life-cycle costs for a given system.     

A new model for nanofluid conductivity based on the effects of clustering due to Brownian motion

Conductivity values of nanofluids calculated with the model proposed by Nan et al. 1 consistently underestimate the corresponding measured values for 20 sets of experimental data from 12 published studies; thus the conclusion of the recent International Nanofluid Property Benchmark Exercise 2 which stated that it is not necessary to resort to other theories (e.g., Brownian motion, liquid layering, and aggregation) for the interpretation of the INPBE database cannot be generalized. In view of this situation, a new model which takes into account clustering and micro‐convection is proposed and compared with experimental data for five nanofluids (with different particle sizes and a range of particle concentrations) as well as two previously published models. The maximum difference between the predictions of the proposed model and the measured values is 6.7% of the latter. © 2011 Wiley Periodicals, Inc. Heat Trans Asian Res; Published online in Wiley Online Library ( wileyonlinelibrary.com/journal/htj ). DOI 10.1002/htj.20350     

Feedback Spin Exciton Formation in Unconventional Superconductors

The superconducting feedback resonance in inelastic neutron scattering (INS) has now been found in numerous unconventional superconductors of the cuprate, ferropnictide, and heavy fermion classes. The collective spin excitation appears below T _c at an energy less than the quasiparticle threshold with momentum Q provided the gap changes sign under translation by Q. The resonance has been found in the heavy fermion (HF) superconductors CeCu₂Si₂, CeCoIn₅, and UPd₂Al₃, and recently in Fe-pnictide Ba_1−x K _x Fe₂As₂, BaFe_2−x Co _x As₂, BaFe_2−x Ni _x As₂, and FeSe_1−x Te _x compounds and may be a more general phenomenon. Of particular interest is the interaction of the 3d spin exciton with the 4f crystalline electric field (CEF) excitations in rare earth based unconventional superconductors like CeFeAsO_1−x F _x pnictide and Nd_2−x Ce _x CuO₄ cuprate where a coupling between 3d spin resonance and 4f CEF excitations leads to intriguing interaction effects observed experimentally by INS.     

Investigation of forestry wastes: Torrefaction and their thermal properties for use in energy recovery schemes

Three biomasses like Eucalyptus, Azadirachata, and Ficus religiosa were torrefied to investigate the effect of temperature and residence time was investigated on torrefied biomasses for yield, volatile matter, fixed carbon, ash, and Gross calorific value (GCV). Thermogravimetric analysis and Hardgrove grindability index (HGI) of three torrefied samples were studied at optimum conditions of temperature and residence time. According to the results, an optimum temperature was found to be 260°C at 45 min residence time. A maximum GCV of torrefied biomasses of Eucalyptus, Azadirachata, and F. religiosa were found to be 4,301, 3,190, and 3,278 kcal/kg, respectively. According to thermogravimetric analyzer results, the Azadirachata has shown higher weight loss compared to Eucalyptus and F. religiosa during thermogravimetirc study. The weight loss rate for Azadirachata was maximum to nearly 12.8%/min compared to 6.11 and 5.12%/min for Eucalyptus and F. religiosa, respectively. The order of reactivity based on mean reactivity and combustion characterization factor was found to be Azadirachata indica > Eucalyptus > F. religiosa. According to HGI results, Eucalyptus, Azadirachata, and F. religiosa have shown HGI values of 71, 60.7, and 81.7, respectively. The results of this study could be useful for the energy recovery schemes in the country.     

Study on microstructure,rheological, and mechanical properties of cellulose short fiber reinforced TPVs based on EPDM/PP

The morphology, rheology, and mechanical properties of the dynamically vulcanized thermoplastic elastomer based on EPDM/PP (60/40, w:w) containing 5, 10, and 20% of cellulose short fiber were studied. From the results it was found that addition of 5% of cellulose fiber has no significant effect on the maximum torque associated with the dynamic vulcanization stage, while higher concentration of fibers decreased the maximum torque. These results were explained in terms of influence of cellulose fibers on the extent of agglomeration formed between the cured rubber particles. The results of tensile test performed on the samples showed that incorporation of 5% of cellulose fibers into the sample has an increasing effect on elongation at break with no appreciable change in tensile behavior. However increasing the cellulose fibers content of the sample to 20% had a remarkable change in tensile properties of the sample resulting in a toughened plastic type behavior. The melt elasticity of the sample containing 5% of cellulose fibers particularly at low shear rate range was found to be lower than that of the sample without fibers indicating the role of fibers in weakening of cured rubber particle agglomeration. This was supported with the results of the relaxation time distribution H(λ) and scanning electron microscopy of the samples. POLYM. COMPOS., 2009. © 2008 Society of Plastics Engineers