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Abstract Timed injection of coolant during the onset of the compression stroke in a reciprocating compressor aimed at achieving quasi-isobaric conditions during the initial part of the compression stroke was investigated as a means of improving compressor efficiency. It is found that an isobaric cooling process followed by an isothermal compression process requires less energy than an isothermal compression process for the same boundary conditions. Achieving isobaric cooling in a real reciprocating compressor would require sudden and significant cooling during the onset of compression. A simplified process model of a real reciprocating compressor was created. It modelled the timed cooling process as a polytropic process with reduced polytropic index. An experimental compressor, equipped with a coolant injection system, was constructed. Dry baseline tests and tests with continuous and timed coolant injection were conducted. It was found that timed injection during the onset of compression, while also keeping the suction valve closed to prevent additional suction air inflow, yields an additional compression work-saving advantage over continuous coolant injection for the same set of boundary conditions. The simplified process model and numerical simulation were validated against the experimental results and were found to agree well with the experimental results.

For many non-renewable resources, reliable production data are only available from a certain point in time but not from the beginning of production periods. In order to constrain the unknown historic production of such resources for those ancient times for which no reliable annual production data are available we present a novel mathematical technique, based on Verhulst’s logistic function. The method is validated by the United States’ crude oil production for which the complete production cycle, starting in 1859, is well documented. Assuming that the oil production in the USA between 1859 and 1929 is unknown, our method yields values for this period of 16.0 gigabarrels (Gb) based on a second-order polynomial fit and 13.5 Gb based on a third-order polynomial fit of post-1929 production data, respectively. Especially the latter amount compares well with the actual value of 12.1 Gb, thus illustrating the strength of the method. For global gold (Au) production, our method yields an ancient production up to the year 1850, when official and reliable production statistics began, of approximately 10,000 metric tons (t) based on a second-order polynomial fit. For mercury (Hg) a production of 64,000 t was determined for the time up to the year 1900, when annual production figures started to become available, again using a second-order polynomial fit. While the results obtained by the application of second-order polynomial functions could be confirmed by higher-order polynomial functions in the cases of both USA oil as well as global Au production, this was not possible in the case of global Hg production because of a highly irregular production curve.

Abstract India’s ever increasing population has made it necessary to develop alternative modes of transportation with electric vehicles being the most preferred option. The major obstacle is the deteriorating impact on the utility distribution system brought about by improper setup of these charging stations. This paper deals with the optimal planning (siting and sizing) of charging station infrastructure in the city of Allahabad, India. This city is one of the upcoming smart cities, where electric vehicle transportation pilot project is going on under Government of India initiative. In this context, a hybrid algorithm based on genetic algorithm and improved version of conventional particle swarm optimization is utilized for finding optimal placement of charging station in the Allahabad distribution system. The particle swarm optimization algorithm re-optimizes the received sub-optimal solution (site and the size of the station) which leads to an improvement in the algorithm functionality and enhances quality of solution. The genetic algorithm and improved version of conventional particle swarm optimization algorithm will also be compared with a conventional genetic algorithm and particle swarm optimization. Through simulation studies on a real time system of Allahabad city, the superior performance of the aforementioned technique with respect to genetic algorithm and particle swarm optimization in terms of improvement in voltage profile and quality.

Abstract Owing to the challenges associated with the application of synthetic/non-modified Botryococcus Braunii Microalgae Biodiesel (BBMB), its poor performance in CI engines has resulted in increased tendencies for non-commercialization of its fuel. The properties of a synthetic BBMB were controlled by acetylene addition. In this study, acetylene was induced with air at mass flow rates of 100, 150, 200 and 300 g/hr in order to monitor the combustion, emission and performance behaviour of a 4-stroke (Kirloskar AV1), 5.2 kW diesel engine with enhanced injection timing, in which the algal biodiesel was introduced as its main fuel. The obtained results compared favourably with those of a conventional dual-fuel CI engine in terms of combustion, emissions and performance. The brake thermal efficiency (BTE) of the acetylated biodiesel improved by 3, 4, 3.6 and 5% due to acetylene addition. NOx emissions were higher for the acetylated-biodiesel, whereas, the release of CO2, HC, and CO were seen to decrease due to the addition of acetylene. Based on the results, the performance, combustion and gaseous emissions of the biodiesel obtained from Botryococcus braunii improved as a result of adding acetylene thus making it a suitable replacement for the conventional diesel fuel used in CI engines.

Abstract The presented derivative thermogravimetric and mass spectral data, obtained simultaneously for the pyrolysis of three different tyre rubbers, corroborate the assumption that the devolatilisation of a tyre rubber proceeds via two consecutive zones of weight loss and that these zones are characterised by different products and thus different reactions. The spectral data of the depolymerisation products moreover confirm that depolymerisation occurs exclusively (in case of polyisoprene rubber) or predominantly (in case of the polybutadiene rubbers) during primary devolatilisation.

The influence of thermal radiation on a two-dimensional non-Newtonian fluid flow past a slendering stretching surface is investigated theoretically. Casson and Williamson fluid models are considered with Soret and Dufour effects. The transformed ODEs are solved numerically using the bvp5c Matlab package and dual solutions are executed for Casson and Williamson fluid cases. The influence of various parameters, namely, thermal radiation parameter, cross diffusion parameters and slip parameters on velocity, thermal and concentration distributions are discussed with the assistance of graphs. The local Nusselt and Sherwood numbers are computed and presented through tables. It is observed that the influence of cross diffusion is higher on Williamson flow when equated with the Casson flow.

Abstract Global humanitarian initiatives are calling for technologies to bridge the urban-rural divide in support of remote community electrification projects through micro-utility programs. Distributed off-grid renewable generation has the ability to supply energy to remote communities while smart microgrids are able to effectively integrate intermittent renewable resources through management procedures that improve reliability, resiliency and sustainability. Microgrid control systems are typified by a hierarchical nature with multi-layered functionalities and capabilities to ensure optimized operations through strategic energy management and power flow balancing. This paper considers transactive energy management principles for supply/demand coordination and demonstrates that the concept is effective in managing energy demand response and data flow dynamics in the context of rural community-based energy systems. A transactive energy management system is modeled for rural village DC microgrids, and evaluated through demonstrative computer simulations. It shows how smart microgrid load control switching on homogeneous load groups is commanded through microgrid economic value signals that are adjustable by home owners to meet village and household energy budget constraints. The proposed approach is novel in that it offers a low complexity coordination framework, based on market principles, and demand response mechanisms for multi-priority grouping control of non-intelligent devices in off-grid rural village settings.

Abstract India has a high potential for technically recoverable biomass, sufficient to meet part of its increasing energy needs, promote energy access in rural and remote areas, create economic opportunities at the national scale, and reduce indoor pollution. Effective utilization of surplus biomass resources is often challenged and hindered by seasonal availability, extensive distribution over vast and distanced areas, and the embedded socio-cultural factors associated with its use. Therefore, the development of reliable maps for the assessment of available/surplus biomass resources is the first key step toward the creation of a new supply chain for cost-effective bioenergy production, particularly in developing countries. In this paper, a new methodological approach that combines primary and secondary data sets, social factors, remote sensing data, and software, such as GIS applications, has been developed. The main goal is to create high-quality, land use/land cover (LULC) maps for agricultural and wastelands in India. With an acceptable level of accuracy assessment, the paper also determines the surplus biomass resources in wastelands and municipal solid waste (MSW) distribution in three Indian states: Madhya Pradesh, Maharashtra, and Tamil Nadu. These states were selected due to the high level of agriculture production and thus high agro-biomass potential, the presence of large industrial agglomerations, and the high interest in bioenergy development in these states. The maps show that the highest surplus biomass from wastelands exists in Madhya Pradesh, while high MSW potentials exist in Maharashtra state. The developed maps considered the existing uses of biomass in order to calculate the surplus biomass resources. The presented maps are a useful tool to optimize the locations of biomass-based and/or co-generation power plants in the surveyed states.