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Optimizing Sustainability:Exergoenvironmental Analysis of a Multi-Effect Distillation with Thermal Vapor Compression System for Seawater Desalination
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作者 Zineb Fergani Zakaria Triki +5 位作者 Rabah Menasri Hichem Tahraoui Meriem Zamouche Mohammed Kebir Jie Zhang Abdeltif Amrane 《Frontiers in Heat and Mass Transfer》 EI 2024年第2期455-473,共19页
Seawater desalination stands as an increasingly indispensable solution to address global water scarcity issues.This study conducts a thorough exergoenvironmental analysis of a multi-effect distillation with thermal va... Seawater desalination stands as an increasingly indispensable solution to address global water scarcity issues.This study conducts a thorough exergoenvironmental analysis of a multi-effect distillation with thermal vapor compression(MED-TVC)system,a highly promising desalination technology.The MED-TVC system presents an energy-efficient approach to desalination by harnessing waste heat sources and incorporating thermal vapor compression.The primary objective of this research is to assess the system’s thermodynamic efficiency and environmental impact,considering both energy and exergy aspects.The investigation delves into the intricacies of energy and exergy losses within the MED-TVC process,providing a holistic understanding of its performance.By scrutinizing the distribution and sources of exergy destruction,the study identifies specific areas for enhancement in the system’s design and operation,thereby elevating its overall sustainability.Moreover,the exergoenvironmental analysis quantifies the environmental impact,offering vital insights into the sustainability of seawater desalination technologies.The results underscore the significance of every component in the MED-TVC system for its exergoenvironmental performance.Notably,the thermal vapor compressor emerges as pivotal due to its direct impact on energy efficiency,exergy losses,and the environmental footprint of the process.Consequently,optimizing this particular component becomes imperative for achieving a more sustainable and efficient desalination system. 展开更多
关键词 Exergoenvironmental analysis MED-TVC DESALINATION environmental impact of freshwater multi-objective optimization
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Study of thin Films of Nickel Oxide (NiO) Deposited by the Spray Pyrolysis Method
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作者 Antar Bouhank Youcef. Bellal Hacene Serrar 《Journal of Chemistry and Chemical Engineering》 2018年第3期116-120,共5页
In this work,thin films of nickel oxide(NiO)were deposited by a simple and inexpensive technique,which is spray pyrolysis on ordinary glass substrates heated to a fixed temperature of500°C,from a solution contain... In this work,thin films of nickel oxide(NiO)were deposited by a simple and inexpensive technique,which is spray pyrolysis on ordinary glass substrates heated to a fixed temperature of500°C,from a solution containing nickel nitrate hexahydrate as a precursor dissolved in distilled water with deferent values of concentrations.The NiO thin films obtained were characterized to determine the structure with X-ray diffraction technique(XRD),the absorption domain(UV-Visible Spectroscopy),and the surface morphology(SEM).The X-ray diffraction patterns confirm the presence of NiO phase with preferential orientation along the(111)direction.The optical gap for nickel oxide calculated with a concentration of0.1M from the measurement of optical absorption is3.6eV,which is quite comparable to the value of the ratio. 展开更多
关键词 NiO thin FILMS SPRAY PYROLYSIS
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Automated synthesis of steady-state continuous processes using reinforcement learning 被引量:2
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作者 Quirin Göttl Dominik GGrimm Jakob Burger 《Frontiers of Chemical Science and Engineering》 SCIE EI CSCD 2022年第2期288-302,共15页
Automated flowsheet synthesis is an important field in computer-aided process engineering.The present work demonstrates how reinforcement learning can be used for automated flowsheet synthesis without any heuristics o... Automated flowsheet synthesis is an important field in computer-aided process engineering.The present work demonstrates how reinforcement learning can be used for automated flowsheet synthesis without any heuristics or prior knowledge of conceptual design.The environment consists of a steady-state flowsheet simulator that contains all physical knowledge.An agent is trained to take discrete actions and sequentially build up flowsheets that solve a given process problem.A novel method named SynGameZero is developed to ensure good exploration schemes in the complex problem.Therein,flowsheet synthesis is modelled as a game of two competing players.The agent plays this game against itself during training and consists of an artificial neural network and a tree search for forward planning.The method is applied successfully to a reaction-distillation process in a quaternary system. 展开更多
关键词 automated process synthesis flowsheet synthesis artificial intelligence machine learning reinforcement learning
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