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Abstract The upward energy demand, along with the depletion of conventional energy sources, demands improved utilization of renewable energy resources. Among all renewable energy resources, solar energy is the most appropriate alternative to conventional energy sources owing to its inexhaustibility and green property. Solar collectors are devices that convert solar radiation into heat or energy. However, the efficiency of the solar collector is still not adequate. The competent step to enhance the efficiency of the solar collector is to use nanofluids. This study is carried out different phases viz. characterization and stabilization while both qualitative and quantitative methods used to evaluate the stability of nanofluids thermophysical properties of Al2O3 and CNC nanofluids such as thermal conductivity measured at four different temperature using KD2 Pro, viscosity and specific heat determined at similar temperature range by viscometer and differential scanning calorimetry respectively. The experiment is executed with a fixed flow rate and in steady-state conditions under extensive solar radiation. The experimental study has revealed that up to 2.48% and 8.46% efficiency of solar collector enhanced by using 0.5% Al2O3 and 0.5% CNC nanofluids respectively. Moreover, nanofluids show good to moderate stability performance. Besides, the thermal conductivity of nanofluids increased while viscosity is in a decreasing trend with increasing temperature. Nanofluids could enhance the efficiency of a flat-plate solar collector.

AbstractWe demonstrate the high concentration exfoliation of graphene nanosheets in dimethyl formamide (DMF) as a solvent from graphite powder. UV-Vis-NIR spectroscopy shows low power bath sonication yields less concentration of graphene nanosheets exfoliation, whereas the high power probe sonication yields high concentration graphene nanosheets exfoliation. The concentration of graphene nanosheets exfoliation depends on amount of energy supplied, and there exists a linear relationship between the concentration of graphene and energy supplied during sonication. TEM micrograph confirms the exfoliation of graphene nanosheets. AFM studies shows; high power sonication for longer time reveals graphene exfoliation with fewer graphene layers. The strategy of bath sonication followed by probe sonication of grapheme solution shows the stable suspension of graphene nanosheets even after one month.

Our aim was to model the current and future potential global distribution of Chloris truncata (windmill grass) based on the plant's biology, soil requirements and colonisation success. The growth response of C. truncata to constant temperatures and soil moisture levels were measured and estimated respectively, to develop parameters for a CLIMEX bioclimatic model of potential distribution. The native distribution in eastern Australia and naturalised distribution in Western Australia was also used to inform the model. Associations with soil types were assessed within the suitable bioclimatic region in Australia. The global projection of the model was tested against the distribution of soil types and the known successful and failed global introductions. The verified model was then projected to future conditions due to climate change. Optimal temperature for plant development was 28°C and the plant required 970 degree-days above a threshold of 10°C. Early collection records indicate that the species is native to Queensland, New South Wales and Victoria. The plant has been introduced elsewhere in Australia and throughout the world as a wool contaminant and as a potential pasture species, but some of the recorded establishments have failed to persist. The CLIMEX model projected to the world reflected effectively both the successful and failed distributions. The inclusion of soil associations improved the explanation of the observed distribution in Australia, but did not improve the ability to determine the potential distribution elsewhere, due to lack of similarity of soil types between continents. The addition of a climate change projection showed decreased suitability for this species in Australia, but increased suitability for other parts of the world, including regions where the plant previously failed to establish.

Co-generation of energy derived from human movement is not new. Intentionally accumulating energy, from mass urban-mobility, provides opportunities to re-purpose power. However, when mass-mobility is predictable, yet not harnessed, this highlights critical gaps in application of interdisciplinary knowledge. This research highlights a novel application of geostatistical modelling for the built environment with the purpose of understanding where energy harvesting infrastructure should be located. The work presented argues that advanced Geostatistical methods can be implemented as an appropriate method to predict probability distribution, density, clustering of populations and mass-population mobility patterns from large-scale online distributed and heterogeneous data sets published by the Australian Urban Research Infrastructure Network. Where clear urban spatio-behavioural relationships of density and movement can be predicted – understanding such patterns supports cross-disciplinary city planning and decision-making. A data-informed – predictive spatial decision-making framework is proposed – facilitating the endeavour of cogenerating kinetic human energy within a prescribed space. This novel proposition could further sustainability strategies for compact living for cities such as in Perth, Western Australia which is increasingly economically and geographically pressured to densify. This research argues that surveillance data elucidate a capacity to interpret and understand impacts of densification strategies, efficacy of CCTV networks in existing and emerging cities.

AbstractEnhancing the efficiency of the electric vehicle’s powertrain becomes a crucial focus, wherein the control system for the traction motor plays a significant role. This paper presents a novel electric vehicle traction motor control system based on a robust predictive direct torque control approach, an improved version of the conventional DTC, where the traditional switching table and the hysteresis regulators are substituted with a predictive block based on an optimization algorithm. Additionally, a robust predictive speed loop regulator is employed instead of the proportional-integral regulator, which integrates a new cost function with a finite horizon, incorporating integral action into the control law based on a Taylor series expansion. This technique’s primary benefit is its independence from the necessity to measure and observe external disturbances, as well as uncertainties related to parameters. The effectiveness of the suggested system was confirmed through simulation and experimental results under the OPAL-RT platform. The findings indicate that the proposed approach outperforms the conventional method in terms of rejecting disturbances, exhibiting robustness to variations in parameters, and minimizing torque ripple.

The main objective of this paper is to evolve an Intelligent Model which can help organizations to restructure their website so that website structure can be refined and it becomes more efficient and user friendly. In order to reach the main goal web mining process, web mining algorithm are applied. These can help to suggest the possible changes in the design of the wesite so that a common user feels much more comfortable in browsing the website. The data for this paper has been collected from a university website using a web crawler. Web mining algorithm are applied on the data so that possible changes can be suggested. General Terms Web Mining, Web Structure Mining, Page Rank, Page Rank Algorithm, Crawlers, Websites.

In the current situation with the unprecedented deployment of clean technologies for electricity generation, it is natural to expect that storage will play an important role in electricity networks. This paper provides a qualitative methodology to select the appropriate technology or mix of technologies for different applications. The multiple comparisons according to different characteristics distinguish this paper from others about energy storage systems. Firstly, the different technologies available for energy storage, as discussed in the literature, are described and compared. The characteristics of the technologies are explained, including their current availability. In order to gain a better perspective, availability is cross-compared with maturity level. Moreover, information such as ratings, energy density, durability and costs is provided in table and graphic format for a straightforward comparison. Additionally, the different electric grid applications of energy storage technologies are described and categorised. For each of the categories, we describe the available technologies, both mature and potential. Finally, methods for connecting storage technologies are discussed.