Multiobjective optimisation of hybrid wind-PV-battery-fuel cell-electrolyser-diesel systems : An integrated configuration-size formulation approach

Acknowledgment The financial support by Energy Renewable UK Ltd through co-funding of REST4U project is gratefully acknowledged.Peer reviewedPostprin

Effects of altitude on the soot emission and fuel consumption of a light-duty diesel engine

A four-cylinder, direct-injection (DI) diesel engine was used to study the effects of altitude on the variations of the exhaust soot emission and engine performance. The experiments were conducted in Mashhad, Iran, at an altitude of 975 m above sea level. A three-lobe rotary blower of Roots type was employed in order to simulate the altitudes down to 350 m by increasing the inlet manifold pressure of the engine. The tests were performed based on the ECE-R49 test cycle, and for each testing point, the experiments were repeated for five boosting pressures which correspond to five different altitudes. Results indicate that with increasing the altitude from 350 m to 975 m, the soot emission increases about 40%. This increase is due to the relatively lower the air density introduced into the cylinders in higher altitudes that leads to the increase of autoignition delay time which could shorten the late combustion phase; hence, the soot burnout process deteriorates. Also it was found that at low engine loads, the Brake-Specific Fuel Consumption (BSFC) increases about 20% with raising the altitude from 350 m to 975 m. At higher loads, the raising rate of fuel consumption is insignificant. The effects of altitude on the other engine parameters such as induced air mass flow rate, volumetric efficiency, equivalence ratio, and exhaust temperature were investigated as well. In addition, a sensitivity analysis was conducted and the results revealed that among the engine parameters, the soot emission alteration has the most sensitivity to the change of the altitude

The effects of fin parameters on the solidification of PCMs in a fin-enhanced thermal energy storage system

In the present study, a triplex-tube, employing fin-enhanced phase change materials (PCMs), as a thermal energy storage (TES) system was studied numerically. The main flaw of the PCMs is their low thermal conductivity that restricts their e ectiveness for energy storage applications. Metallic (copper) fins are added to the geometry of the system to improve their function by extending the heat transfer area. The e ects of the presence, configuration, and dimensions of copper fins were investigated to understand the best design for minimizing the solidification time and achieving the best performance enhancement for the TES system selected for this study. The results revealed that the best performance belonged to fins with a mix configuration, with an attachment angle of 90 and the length and width of 28 mm and 1 mm, respectively. Using this configuration could reduce the required time for complete solidification by around 42% compared to the system without fins. Moreover, it was concluded that increasing the length of the fin could o er its positive e ect for enhancing the performance of TES system up to an optimal point only while increasing the width showed a diverse influence. Furthermore, the angles between the tube surface and the fin direction were investigated and 90 was found to be the best choice for the TES case selected in this study. In addition, placement of the fins on the surface of internal or external tube or mix method did not show a significant e ect while placing the fins on the external surface of the tube showed even a negative impact on the performance of the TES system compared with when no fins were applied.http://www.mdpi.com/journal/energiesam2020Mechanical and Aeronautical Engineerin

Machine learning in biohydrogen production: a review

Biohydrogen is emerging as a promising carbon-neutral and sustainable energy carrier with high energy yield to replace conventional fossil fuels. However, biohydrogen commercial uptake is mainly hindered by the supply side. As a result, various operating parameters must be optimized to realize biohydrogen commercial uptake on a large-scale. Recently, machine learning algorithms have demonstrated the ability to handle large amounts of data while requiring less in-depth knowledge of the system and being capable of adapting to evolving circumstances. This review critically reviews the role of machine learning in categorizing and predicting data related to biohydrogen production. The accuracy and potential of different machine learning algorithms are reported. Also, the practical implications of machine learning models to realize biohydrogen uptake by the transportation sector are discussed. The review indicates that machine learning algorithms can successfully model non-linear and complex interactions between operational and performance parameters in biohydrogen production. Additionally, machine learning algorithms can help researchers identify the most efficient methods for producing biohydrogen, leading to a more sustainable and cost-effective energy source

Evaluation of clustering role versus Brownian motion effect on the heat conduction in nanofluids: A novel approach

In this study, the temperature and viscosity-dependent methods were used to identify the main heat conduction mechanism in nanofluids. Three sets of experiments were conducted to investigate the effects of Brownian motion and aggregation. Image processing approach was used to identify detailed configurations of different nanofluids microstructures. The thermal conductivity of the nanofluids was measured with respect to the dynamic viscosity in the temperature range between 0 and 55 °C. The results clearly indicated that the nanoparticle Brownian motion did not play a significant role in heat conduction of nanofluids, which was also supported by the observation that a more viscous sample rendered a higher thermal conductivity. Moreover, the microscopic pictures and the differences in the viscosity between theoretical and experimental values suggested the major role of particle aggregation and clustering

Preface

International audience2021 International Conference on Fluid and Chemical Engineering (ICFCE 2021) was scheduled to be held in Wuhan, China during October 29-30, 2021. Due to the continuing effect of Covid-19 epidemic, after the discussion of the conference committee, ICFCE 2021 will be postponed to be held on 19th November 2021 as an online conference. Organized by Hubei Zhongke Institute of Geology and Environment Technology, ICFCE 2021 intends to invite worldwide famous scientists, experts, scholars, and researchers for academic presentations. ICFCE 2021 proceeding is a collection of outstanding submissions in the field of biofluid mechanics, chemically reacting fluids and combustion, computational fluid dynamics (CFD), experimental fluid mechanics, flow through porous media, fluidsolid interactions (FSI), geophysical fluid dynamics, granular/suspension flows, heat and mass transfer, hydrodynamics, physical, theoretical and computational chemistry, chemical engineering fundamentals, chemical reaction engineering, chemical engineering equipment design and process design, thermodynamics, catalysis & reaction engineering, particulate systems, crystallization, etc. 28 articles were selected from 58 submissions after peer-review, and authors participated in ICFCE 2021 with oral presentations and posters, promoting the communication among researchers and experts from institutes and universities, including Dalian University of Technology, Liaoning University of Technology School of Mechanical Engineering and Automation, University of Science and Technology of China, China North Engine Research Institute, etc. Cordial gratitude is delivered to Technical Program Committee of ICFCE 2021 for the professional work on guarantying the high standard of conference as well as the proceedings. We believe the proceedings will enhance the exchange of ideas and state-of-art knowledge on Fluid and Chemical Engineering. List of Technical Committee, Chair, Editor, International Committee Members are available in this pdf

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