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This paper describes a study of the combustion process in an industrial radiant tube burner (RTB), used in heat treating furnaces, as part of an attempt to improve burner performance. A detailed three-dimensional Computational Fluid Dynamics model has been used, validated with experimental test furnace temperature and flue gas composition measurements. Simulations using the Eddy Dissipation combustion model with peak temperature limitation and the Discrete Transfer radiation model showed good agreement with temperature measurements in the inner and outer walls of the burner, as well as with flue gas composition measured at the exhaust (including NO). Other combustion and radiation models were also tested but gave inferior results in various aspects. The effects of certain RTB design features are analysed, and an analysis of the heat transfer processes within the burner is presented.

Achieving carbon-neutrality has become a global agenda following the ratification of the Paris Agreement. For the developing countries, in particular, attaining a low-carbon economy is particularly important since these economies are predominantly fossil-fuel dependent, to which Bangladesh is no exception. Therefore, this study specifically aimed at evaluating the environmental impacts associated with energy consumption and other key macroeconomic variables in the context of Bangladesh over the 1975-2016 period. As opposed to the conventional practice of using carbon dioxide emissions to proxy environmental quality, this study makes a novel attempt to use the carbon footprints to measure environmental welfare in Bangldesh. The outcomes from this study are expected to facilitate the carbon-neutrality objective of Bangladesh and, therefore, enable the nation to comply with its commitments concerning the attainment of the targets enlisted under the Paris Agreement and the United Nations Sustainable Development Goals declarations. The econometric analysis involved the application of methods that are suitable for handling the structural break issues in the data. The overall findings from empirical exercises reveal that aggregate energy consumption, fossil fuel consumption, and natural gas consumption boost the carbon footprint figures of Bangladesh. In contrast, nonfossil fuel consumption and hydroelectricity consumption are witnessed to abate the carbon footprint levels. Besides, economic growth and international trade are also evidenced to further increase the carbon footprints. Hence, these findings suggest that a clean energy transition within the Bangladesh economy can be the panacea to the nation's persitently aggravating environmental hardships. Furthermore, the causality analysis confirmed the presence of unidirectional causalities stemming from total energy consumption, fossil fuel consumption, natural gas consumption, hydroelectricity consumption, economic growth, and international trade to the carbon footprints. On the other hand, nonfossil fuel consumption is found to be bidirectionally associated with carbon footprints. In line with these aforementioned findings, several key policy suggestions are put forward regarding the facilitation of the carbon-neutrality agenda in Bangladesh.

Abstract This paper uses analytical hierarchy process (AHP) methodology to perform a comparison between the different electricity power production options in Jordan. The systems which were considered, in addition to fossil fuel power plants, are nuclear, solar, wind, and hydro-power. Results on cost-to-benefit ratios show that solar, wind, end hydro-power may be the best alternatives for electric power production. Nuclear electricity turns out to be the worst choice, followed by fossil fuel electric power.

Abstract Heavy oil resources, as a non-renewable energy resource, often require extra enhanced oil recovery techniques such as solvent-based processes. Many kinds of solvents including pure and mixed solvents have been tested in solvent-based applications. Compared with pure solvent, the solvent mixture has the advantage of relatively higher dew point pressure while maintaining desirable solubility in heavy oil. The characterization of foamy oil behavior in a pure solvent system is different from that of the solvent mixture system despite their similarities. Thus, an additional numerical simulation study is necessary for the solvent mixture system. This work conducted simulation studies to investigate foamy oil behavior in a heavy oil-mixture solvent (C1 + C3) system from pressure depletion tests. A better understanding of foamy oil characterization and mechanism in a heavy oil-mixture solvent system is obtained. A reliable non-equilibrium model is developed to perform simulation studies. Since previous experiments suggest the behavior of foamy oil in the solvent mixture system share similarities with the heavy oil-methane system, this investigation first conducted a simulation study with consideration of two reactions in the model and achieved good agreements between the simulated calculation results and experimentally measurement. Then, four reactions are considered in the model for simulation study and obtained better history match results. The simulation results suggest methane has more impact on the foamy oil behaviors than propane in the heavy oil-mixture solvent system. This work also discussed the effect of model parameters involved in the history matching process and conducted sensitivity analysis.

When integrating intermittent renewable energies in the electricity system, additional technologies are needed to ensure that a sufficient power supply is maintained. Alongside storage technologies and conventional power plants, dispatchable biogas plants are one solution for balancing demand and supply in energy systems with a high proportion of renewable energies. In this study, we conducted an economic assessment of the different extension paths and modes of operation of the biogas plants in Germany's future electricity system for the period of 2016–2035. This entailed carrying out a cost-benefit analysis that included the costs incurred for the flexibilization and installation of new biogas plants and the costs saved with respect to onshore wind turbines and additional saved opportunity costs. The results show that adding biogas plants in Germany's future electricity system –compared to their phase-out– requires cost reductions and/or has to be accompanied by further benefits in other sectors and areas to ensure economically feasible operation. Differentiated from a substantial growth, higher net present values were obtained in the extension path characterized by a low construction rate of new biogas plants. Furthermore, the economic feasibility of biogas plants benefits from an early phase-out of lignite- and coal-fired power plants.

Abstract This paper proposes two one-dimensional (1D) convolutional neural networks (CNNs) for predicting dominant wind speed and direction for the temporal wind dataset. The proposed 1D Single CNN (1DS) takes as input the consecutive temporal values in terms of the wind speed and direction and predicts in future dominating speed and direction, separately, after the last value in the input. The developed 1D Multiple CNN (1DM) combines several 1DS but with different views of the same input, therefore, learning more information compared to the 1DS. The proposed algorithms have been trained and tested using the historical wind datasets of Stuttgart (Germany) and Netherlands for different months. Total accuracies reached up to 95.2%, 95.1% for predicting the dominant wind speed and direction, respectively, using the 1DS and up to 98.8%, 99.7% for predicting the dominant wind speed and direction, respectively, using the 1DM. Unlike other methods which use regression techniques with manually designed features for predicting speed and direction, the proposed methods have used classification techniques with the 1DS and 1DM learning their features automatically on original wind dataset. Further, predicted dominant speed and direction in this work would be helpful in wind turbine installation whose power output depends on above parameters.

Abstract In this investigation, spectroscopic (FT-IR, UV–Vis, 1 H NMR) and chromatographic (GC) techniques were used to analyze two Jordanian shale oils, Sultani and El-Lajjun. The oils were extracted at different pyrolysis temperatures (400–500 °C) using a fluidized bed reactor. The spectroscopic and chromatographic analyses show that the variation of pyrolysis temperature has no significant effect on the composition of the produced oil. The 1 H NMR results indicate that the protons of methyl and methelyene represent the bulk of the hydrogen (∼90%) in most shale oil samples. GC analysis reveals that the oil samples contain n-alkanes with a predominant proportion of n-C25.

Millions of air conditioning units consume about 60-64 % of total produced electrical energy in GCC Countries in the summer season. Conditioning the air involves taking the heat out and also extracts moisture (humidity) out of the air. This dehumidification process utilizing the evaporator of air conditioning units could be an alternative and sufficient means to obtain fresh distilled water. There is a strong potential for condensate collection technology to impact water shortages in the regions of the world where suitable conditions exist.This paper presents case study analysis of experimental investigation and practical application of the amount of condensed fresh water can be collected and utilized from the discharge pipe of a two tones of refrigeration indoor air conditioning unit installed in a house during the summer season in the Kingdom of Bahrain. Up to 7 liters/hour of freshwater was obtained with an overall average rate of 2.07 Liters/hour. The study gives a good prediction of the amount of condensed fresh water output for particular indoor relative humidity.