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The work presented herein reports on the investigation of the biogas dry reforming catalytic performance of LaNiO3 (LNO), La0.8Sm0.2NiO3 (LSNO), La0.8Pr0.2NiO3 (LPNO) and La0.8Ce0.2NiO3 (LCNO). The perovskite-type materials were synthesized via citrate sol-gel and characterized using XRD, N2 physisorption H2-TPR, H2-TPD, TEM, HAADF-STEM and XPS. The performance of all catalysts in terms of both activity and stability was examined in order to assess the effect of temperature on the CH4 and CO2 conversion, as well as on the H2 and CO yield and the H2/CO molar ratio of the produced gas mixture. Experimental results showed that modification of LaNiO3 with Sm and Pr enhanced the catalytic performance in terms of catalytic stability and reduced the order/crystallinity of the deposited coke. A theoretical model was also produced in Python with the purpose of simulating the catalytic performance. Modelling results showed a good agreement with the experimental values and therefore confirm the validity of the model for predicting the dry reforming catalytic performance.

Abstract A Wells turbine is one of the simplest and promising self-rectifying air turbines which is basic to the needs of the near future and likely to be economically viable. With the recent development in computer hardware and software, it has now become practicable to conduct a reasonable computation of three-dimensional turbulent flows through complex geometry. To investigate the effect of blade sweep on the performance of the Wells turbine, the numerical investigation was carried out under steady flow condition with a fully 3-D Navier–Stokes code for two kinds of blades, NACA0020 and CA9. As a result, it was found that the performance of the Wells turbine is considerably influenced by the blade sweep. The optimum blade sweep ratio (f=0.35) for the NACA0020 was found. This value is just the same as one obtained experimentally by the authors in the past. It was also found that the overall turbine performance for the NACA0020 is better than that for the CA9. It was shown that the numerical method is able quite well to predict the effect of blade sweep of the Wells turbine. The detailed flow patterns for several blade sweeps were also shown and discussed in this paper.

Abstract Anaerobic digestion (AD) is a long-established method for treating wastewater sludge and has been extensively researched, but there remains a lack of generic or practical modelling tools to guide operators and maximise the energy output. Detailed kinetic models have been developed, but are too complex as practical tools for industrial level application. A multi-level model of biogas yield (BY) was therefore developed based on operational data from 72 full-scale sites in the UK showing a wide range of AD performance. The model focused on the controllable operational parameters that are currently monitored at full-scale, including: temperature, hydraulic retention time and dry solids content in the feed sludge. The model effectively described performance variations in BY of full-scale processes, and provides a practical management tool to aid decision support to improve AD efficiency and net energy balance.

Solar Photovoltaic Water Pumping (SPVWP) systems have established their potential as the most dependable and economically viable systems compared to the diesel based or grid-based electrical pumps. This paper presents an in-depth investigation of the energy efficiency of SPVWP system based on solar radiation, temperature, and operational heads. The study also identifies the shortcomings in the conventional design method based on Best Efficiency Point (BEP) concept that is applicable only in case of fixed frequency and voltage type pumps. However, in the case of SPVWP systems, due to variations in the solar intensity, ambient temperature, and water head, BEP concept does not offer the best efficiency design. The study experimentally proves that the model based on weighted system efficiency and Solar Operational Duty Head (SODH) increases the performance of SPVWP system (∼9% gain) and is consistently provide higher efficiencies in any season or under any climatic conditions.

Abstract Waste-to-energy (WTE) technologies convert municipal solid, and biomass wastes into affordable renewable heat and power energy. However, there are large uncertainties associated with using waste feed as a renewable energy source. This paper proposes a WTE management tool that provides forecasting and real-time optimization of power generated with the consideration of anomaly. The WTE management framework was designed based on a biological neural network, the Hierarchical Temporal Memory (HTM) coupled with a dual-mode optimization procedure. The HTM model is inspired by the mechanism in the cerebral neocortex of the brain, providing anomaly identification and spatial-temporal prediction. In this work, the HTM-based smart energy framework is demonstrated in an industrial case study for the power generation of a waste-to-energy cogeneration system. HTM was compared with methods such as Long Short-Term Memory (LSTM) neural network, Autoregressive Integrated Moving Average (ARIMA), Fourier Transformation Extrapolation (FTE), persistence forecasting, and was able to achieve mean squared error (MSE) of 0.08466% while giving 35450 Euro profit in half a year. Coupled with a novel dual-mode optimization procedure, HTM demonstrated 11% improvement with respect to only predictive optimization (with HTM) in estimated gross profit.

In the pursuit of renewable sources of energy, biomass is emerging as a promising resource because of its abundance and carbon neutral nature. Pyrolysis is a prevailing technology for biomass conversion into the valuable hydrocarbon and alternative fuels. In this review, pyrolysis of lignocellulosic biomass has been addressed, focusing primarily on the ideal feedstock, technologies, reactors, and properties of the end product. Technical problems in using biofuel from pyrolysis, as transport fuel have also been discussed, along with solutions to address these challenges, and comments on the future scope of the pyrolysis process.

Abstract The contact resistance between the gas diffusion layer (GDL) and the bipolar plate has been experimentally estimated as they are assembled in proton exchange membrane (PEM) fuel cells. A number of coated and non-coated GDLs, graphite bipolar plates and a sealing gasket were employed to perform the test. The results show that the contact resistance of the non-coated GDLs (or carbon substrates) is highly influenced by the competing effects of the initial thickness of the GDL and the polytetrafluoroethylene (PTFE) loading. As for the coated GDLs, the PTFE loading present in the microporous layer (MPL) was found to play a positive role in establishing a good contact between the GDL and the bipolar plate.

Abstract Experiments are carried out on a R11 vapour jet refrigeration system (VJRS) to study the influence of ejector configuration and operating conditions on the performance. Eight ejector configurations, formed out of five nozzles and seven diffusers are investigated. The influence of boiler temperature, which represents the solar energy collection temperature, and that of evaporating temperature, which denotes the cooling load temperature, are studied. Overall COPs in the range of 0.08-0.33 and evaporating temperatures in the range of −3–18°C are obtained for boiler temperatures from 75 to 85°C. Ejector configuration has significant influence in deciding the operating range.