Impact of HHO gas enrichment and high purity biodiesel on the performance of a 315 cc diesel engine

Biodiesel and oxyhydrogen (HHO) gas have shown promising results in improving engine performance and emissions. In this work, the effects of HHO gas and 5% biodiesel blends (B5) and their combined use in a 315 cc diesel engine have been analyzed. Biodiesel is produced by base catalyzed transesterification and cleaned by emulsification. Its calculated cetane index (CCI) was 61.4. HHO gas is produced from electrolysis of concentrated potassium hydroxide solution. The use of 5% biodiesel blend resulted in a significant rise of 9.4% in the brake thermal efficiency (BTE) and a maximum reduction of 8.19% in the brake specific fuel consumption (BSFC). HHO enrichment of diesel and biodiesel at 2.81 L/min through the intake manifold improved the torque and power by an average of over 3%. HHO addition also improved the BTE of diesel by a maximum of 3.67%. The combination of high CCI biodiesel fuel and HHO creates a mixture that has shortened the ignition delay (ID) to the point that adverse effects were observed due to the premature combustion as shown by the average decrease in the BTE of 2.97% compared to B5. Thus, B5, on its own, is found to be the optimum fuel under these conditions.     

A non-parametric double homogeneously weighted moving average control chart under sign statistic

In practical situations, the underlying process distribution sometimes deviates from normality and their distribution is partially or completely unknown. In that instance, rather than staying with/depending on the conventional parametric control charts, we consider non-parametric control charts due to their exceptional performance. In this paper, a new non-parametric double homogeneously weighted moving average sign control chart is proposed with the least assumptions. This chart is based on a sign test statistic for catching the smaller deviations in the process location. Run-length (RL) properties of the proposed chart are studied with the help of Monte Carlo simulations. Both in-control and out-of-control RL properties show that the proposed chart is a better contender as compared to some existing charts from the literature. A real-life application for practical consideration of the proposed chart is also provided.     

Principal component analysis and correlation studies of spring wheats in relation to cookie making quality

Quality of cookies is profoundly influenced by the physicochemical and rheological properties of wheat grains. Therefore, it is pivotal to explore right choice of wheat cultivar. Current study was designed to gauge the relationship between wheat grain physiognomies and flour rheological behaviour with cookie characteristics. The outcomes depicted that selected wheat varieties varied significantly (p < 0.01) in various parameters like thousand kernel weight, test weight, pearling value, Pelshenke and zeleny value. In correlation, particle size index correlated negatively (r = ?0.67) with protein content and positively with water absorption. Spread factor of cookies was influenced by particle size index (r = ?0.63), Pelshenke (r = ?0.62), water absorption (r = ?0.60), and mixographic peak height (r = 0.85). Principal component analysis illustrated that thousand kernel weight, grain length, and width were major components in determining the water absorption of wheat flour. However, spread factor of cookies was partly depicted from Pelshenke value and partly from particle size index.     

Analysis of trace impurities in hydrogen: Enrichment of impurities using a H2 selective permeation membrane

A laboratory-scale gas sampling and impurity enrichment device (GSIED) using a Pd/Cu-coated Pd–Ag alloy hydrogen selective permeation membrane has been designed, fabricated, and tested to show that such a device provides an effective method to enrich trace impurity species in hydrogen by factors of 10–100 or greater. The enrichment process will allow analysis of these impurities in hydrogen using simpler and less expensive analytical instruments that can be deployed in the fields. A series of experiments was conducted with the device using a hydrogen analyte gas containing N₂, CH₄, and CO₂ at ∼0.1% each, CO at ∼100 ppm, and H₂S at ∼2 ppm. Chemical analyses of the impurity-enriched sample showed that for the non-sulfur species, the measured enrichment factors were 14.5–14.9, which closely matched the calculated enrichment factors of 14.8–14.9. The elemental material balances indicated a good accounting of the non-sulfur impurity species. For the sulfur species, some initial sulfur loss was observed, presumably due to interaction with the surfaces and/or analytical deficiencies. The impurity enrichment factors for such sampling devices are functions of the sampler size, and the sample vessel pressures before and after enrichment. Depending on the volume of the enriched sample needed for analysis, the device can be designed to enrich the impurities in hydrogen by more than a factor of two orders of magnitude for practical and economical field applications.     

The Use of Probability Limits of COM–Poisson Charts and their Applications

The conventional c and u charts are based on the Poisson distribution assumption for the monitoring of count data. In practice, this assumption is not often satisfied, which requires a generalized control chart to monitor both over‐dispersed as well as under‐dispersed count data. The Conway–Maxwell–Poisson (COM–Poisson) distribution is a general count distribution that relaxes the equi‐dispersion assumption of the Poisson distribution and in fact encompasses the special cases of the Poisson, geometric, and Bernoulli distributions. In this study, the exact k‐sigma limits and true probability limits for COM–Poisson distribution chart have been proposed. The comparison between the 3‐sigma limits, the exact k‐sigma limits, and the true probability limits has been investigated, and it was found that the probability limits are more efficient than the 3‐sigma and the k‐sigma limits in terms of (i) low probability of false alarm, (ii) existence of lower control limits, and (iii) high discriminatory power of detecting a shift in the parameter (particularly downward shift). Finally, a real data set has been presented to illustrate the application of the probability limits in practice. Copyright © 2012 John Wiley & Sons, Ltd.     

A hybrid optimisation model for the synthesis of sustainable gasification-based integrated biorefinery

Depletion of fossil fuels and increasing public awareness of environmental issues has stimulated the search for alternative energy sources. Biofuels are recognised as one of the most promising alternatives to fossil fuels, as they can be produced from various types of feedstock. The efficiency and sustainability of biomass-based production can be maximised by producing biofuels along with other valuable coproducts in a “biorefinery”. This concept was proposed to make the production of biofuels and biochemicals more economically viable by taking advantage of opportunities for process integration and waste recovery. In this work, a novel hybrid optimisation model that combines superstructure-based optimisation approach and insight-based automated targeting for the synthesis of a sustainable integrated biorefinery is presented. In addition, fuzzy optimisation is also adapted to synthesize such integrated facility with the simultaneous consideration of both economic and environmental performance. Note that the proposed approach is a generic synthesis strategy that can be applied even without detailed modelling of individual processes.     

Full chain energy analysis of fuel ethanol from cane molasses in Thailand

An analysis of energy performance and supply potential was performed to evaluate molasses utilization for fuel ethanol in Thailand. The Thai government recently has set up a production target of 1.925 million litres a day of sugar-based ethanol. The molasses-based ethanol (MoE) system involves three main segments: sugar cane cultivation, molasses generation, and ethanol conversion. Negative net energy value found for MoE is a consequence of not utilizing system co-products (e.g. stillage and cane trash) for energy. Taking into account only fossil fuel or petroleum inputs in the production cycle, the energy analysis provides results in favour of ethanol. A positive net energy of 5.95 MJ/L which corresponds to 39% energy gain shows that MoE is efficient as far as its potential to replace fossil fuels is concerned. Another encouraging result is that each MJ of petroleum inputs can produce 6.12 MJ of ethanol fuel. Regarding supply potential, if only the surplus molasses is utilized for ethanol, a shift of 8–10% sugar cane produce to fuel ethanol from its current use in sugar industry could be a probable solution.     

Intelligent Systems in Optimizing Reservoir Operation Policy: A Review

The paper presents a survey of several optimization techniques, mainly artificial intelligences (AIs) which have been applied to the reservoir operation modelling whether its single or multi-reservoir system. The reservoir system modeling is essential for any nations and the optimal use of it is always asked. The main objective of this review article is to discuss the potentiality of the evolutionary algorithms (EAs) and the ability to integrate with other techniques which can provide the best results. Also the formulation of these types of application has described on the ground of a well known benchmark problem regarding this field. The traditional algorithms got some drawbacks. The study provides a complete understanding to the EA users about next generation optimal search procedure and help to overcome the drawbacks. Though the background of application number of swarm intelligences is less comparatively than the genetic algorithm (GA), it provides a great scope for the researcher for further development. Also comparative results with other popular methods (such as, linear programming, stochastic dynamic programming) are discussed on the basis of past research results. Conclusions and suggestive remarks are made for the help of researchers and the reservoir decision makers as well.     

Characterization of a novel bioactive poly[(lactic acid)‐co‐(glycolic acid)] and collagen hybrid matrix for dermal regeneration

Different strategies have been explored for the purpose of autologous or allogeneic dermal regeneration. We have developed a hybrid matrix by lyophilizing collagen within a poly[(lactic acid)‐co‐(glycolic acid)] (10:90, molar composition) knitted mesh, in order to assimilate the advantages of natural and synthetic materials. The porosity of the mesh was found to be almost 95 %, using Micro‐Computed Tomography Analysis, while the mechanical properties were comparable to native skin. In vitro biocompatibility was analyzed by culturing rat dermal fibroblasts in the matrices over 10 days. The cells were able to attach, proliferate and remain viable within the hybrid matrices. Subsequently, in vivo biocompatibility was analyzed by implanting the matrices subcutaneously in immunocompetent rats, for 2 weeks. Histological analysis showed that the poly[(lactic acid)‐co‐(glycolic acid)]–collagen hybrid matrices evoked minimal host tissue response in vivo. This study forms the basis of using poly[(lactic acid)‐co‐(glycolic acid)]–collagen hybrid matrices for our future work to develop a bioactive matrix for dermal regeneration. Copyright © 2005 Society of Chemical Industry