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Innovative Research in Applied Science, Engineering and Technology (IRASET),Conference on

作者： Jouary Oumaima Bouabid Badreddine Mighouar Zakaria Ech-Chhibat Moulay El Houssine Zahiri Laidi Laboratory of Modeling and Simulation of Intelligent Industrial Systems Hassan II University of Casablanca ENSET of Mohammedia Mohammadia Morocco

ISBN: (数字)9798331532970

ISBN: (纸本)9798331532987

Pipelines play an essential role in the transportation of pressurized fluids over long distances, but their performance can be affected by the presence of leaks. This study aims to analyze the effect of leak intensity on the fluid pressure at the pipeline outlet. Using a numerical model, simulations were conducted to study the influence of the position and intensity of the leaks on the overall behavior of the transportation system. The results obtained allow for a better understanding of the mechanisms intervening, as well as proposals for optimizing pipeline maintenance and safety.

关键词： Technological innovation Fluids Pipelines Transportation Numerical models Safety Maintenance Proposals Sustainable development Predictive maintenance

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Smart Materials Unveiled: From Fundamentals to AI-Driven Innovations

Smart Materials Unveiled: From Fundamentals to AI-Driven Inn...

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Innovative Research in Applied Science, Engineering and Technology (IRASET),Conference on

作者： Hanane Boutraih Abdellah Zamma Naoual Belouaggadia Laboratory of Modeling and Simulation of Intelligent Industrial Systems (M2S2I) ENSET University Hassan II of Casablanca Morocco Laboratory of Modeling and Simulation of Intelligent Industrial Systems (M2S2I) ENSET Hassan II University Mohammedia Morocco Builders Lab Builders École d’ingénieurs COMUE Normandie Université Epron France

ISBN: (数字)9798331532970

ISBN: (纸本)9798331532987

The development of intelligent or smart materials is crucial to meet the demand for modern materials and to solve issues related to durability, performance, cost, resource availability, and environmental impact. Due to their great potential, they can be employed in many different sectors, such as biomedical, automotive, aerospace, civil industries, and energy. These materials are diverse, including piezoelectric materials, shape-memory alloys, magnetostrictive materials, electro- and magnetorheological fluids, chromic materials, and self-healing materials. In this paper, various kinds of intelligent materials are discussed, along with their benefits, limitations, potential uses, and the important role artificial intelligence has played in the progress of smart material research.

关键词： Technological innovation Electric potential Magnetostriction Intelligent materials Piezoelectric materials Metals Magnetic liquids Artificial intelligence Sustainable development Smart materials

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Smart Materials for Energy Efficiency: A Decade of Bibliometric Insights (2014-2024)

Smart Materials for Energy Efficiency: A Decade of Bibliomet...

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Innovative Research in Applied Science, Engineering and Technology (IRASET),Conference on

ISBN: (数字)9798331532970

ISBN: (纸本)9798331532987

Nowadays, Smart Materials and Energy Efficiency are among the most current subjects. For this reason, this article seeks to study the relationship between these two topics through a bibliometric analysis using Scopus and VOSviewer over the last decade (from 2014 to 2024). Based on these tools, 300 researchers wrote 370 published papers from 227 sources that were listed in Scopus. This study presented cumulative data on the number of publications per year, their types, research areas, contributing countries, authors, and keywords. The results of this research are significant as they provide essential information that enhances researchers' understanding of the latest developments and trends in smart materials and energy efficiency.

关键词： Phase change materials Thermoelectric materials Intelligent materials Bibliometrics Market research Three-dimensional printing Energy efficiency Energy harvesting Waste heat Smart materials

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Integration of Artificial Intelligence in Phase Change Materials in Buildings: A Bibliometric Analysis

Integration of Artificial Intelligence in Phase Change Mater...

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Innovative Research in Applied Science, Engineering and Technology (IRASET),Conference on

作者： Wissal Nahairy Omar Bouattane Abdellah Zamma Naoual Belouaggadia Laboratory of Modeling and Simulation of Intelligent Industrial Systems (M2S2I) ENSET University Hassan II of Casablanca Morocco Laboratory of Electrical Engineering and Intelligent Systems (IESI) ENSET University Hassan II of Casablanca Morocco Builders Lab Builders École d’ingénieurs COMUE Normandie Université Epron France

ISBN: (数字)9798331532970

ISBN: (纸本)9798331532987

Artificial intelligence (AI) is a fast-growing technology that has enormous potential to transform many industries, including building energy management. Phase change materials in buildings, which regulate temperature by absorbing or releasing heat during changes in state, can be optimized by AI to improve their efficiency and environmental impact. This study presents the results of a bibliometric analysis of 244 research articles on the integration of artificial intelligence in phase-change materials, from the Scopus database. The analysis was carried out to identify current trends in research in this area, the most studied topics, the most productive authors and the most active countries. The R Studio and VOSviewer tools were used to analyze the publications on the use of artificial intelligence in the optimization of phase change materials and its impact on the thermal management of buildings. This bibliometric analysis makes it possible to visualize the links between publications, keywords, authors and countries, and to identify the main research themes, as well as the most influential authors and sources in this field.

关键词： Phase change materials Technological innovation Databases Bibliometrics Thermal management Market research Thermal analysis Artificial intelligence Optimization Building management systems

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Artificial Intelligence in Solar Stills: A Bibliometric Analysis of Trends, Applications, and Future Prospects

Artificial Intelligence in Solar Stills: A Bibliometric Anal...

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Innovative Research in Applied Science, Engineering and Technology (IRASET),Conference on

作者： Ait Baha Asmaa Omar Bouattane Naoual Belouaggadia Abdellah Zamma Laboratory of Modeling and Simulation of Intelligent Industrial Systems (M2S2I) ENSET Hassan II University of Casablanca Morocco Laboratory of Electrical Engineering and Intelligent Systems (IESI) ENSET Hassan II University of Casablanca Morocco Builders Lab Builders École D’ingénieurs COMUE Normandie Université Epron France

ISBN: (数字)9798331532970

ISBN: (纸本)9798331532987

Solar stills are relatively affordable, renewable energy distillers with low maintenance, which can help solve water problems in remote areas. Artificial intelligence (AI) has enhanced efficiency through adaptive control, the adjustment of operational parameters, and the development of forecasting methods and tools. AI solutions, such as hybrid models and machine learning, enhance design, automate tasks, and reduce costs by optimizing insulation and tilt angle, among other factors. There are also additional complementary technologies, such as nanotechnology and phase change materials, that improve sustainability and performance. In this paper, we review the adoption of artificial intelligence technology in solar still research, utilizing a bibliometric technique to analyze 2216 articles published between 2019 and 2024. The results show that the development of AI-integrated solar still technology experienced significant growth between 2019 and 2024, demonstrating how artificial intelligence enhances the efficiency, design, and performance of solar desalination systems. The findings also reveal that The Journal of Cleaner Production and Desalination are the most prominent sources in this field, driving knowledge dissemination and innovation. Additionally, the results highlight that China, India, and Egypt are the most active contributors to this research domain, reflecting their strong commitment to tackling water scarcity and promoting sustainable desalination.

关键词： Phase change materials Renewable energy sources Technological innovation Bibliometrics Desalination Production Maintenance Artificial intelligence Optimization Nanotechnology

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AI-Optimized Genetic Algorithm for Enhancing Resource Recovery in the Circular Economy

AI-Optimized Genetic Algorithm for Enhancing Resource Recove...

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Innovative Research in Applied Science, Engineering and Technology (IRASET),Conference on

作者： Abderrahman Mansouri Bellat Abdelouahad Idriss Bennis Ali Siadat Fatiha Akef Modeling and Simulation of Intelligent Industrial Systems Laboratory (M2S2I) ENSET Mohammedia Hassan II University Casablanca Morocco Laboratory of Design Manufacturing and Control Arts et Metiers ParisTech Metz France Laboratory of Mechanical and Thermal Processes and Control (PCMT) ENSAM Rabat Mohammed V University in Rabat Morocco

ISBN: (数字)9798331532970

ISBN: (纸本)9798331532987

This paper presents a Genetic Algorithm (GA)- based optimization approach aimed at improving circular economy strategies by optimizing recyclability and economic value, while minimizing disassembly complexity and environmental impact. A multi-objective function is established, incorporating essential parameters such recyclability rate, component reuse value, disassembly expenses, carbon footprint, and waste minimization. The GA investigates an optimal balance between sustainability and economic viability using an evolutionary search method that identifies and enhances solutions throughout several generations. The dataset comprises 50 components of end-of-life products, categorized as metals (40%), plastics (30%), and electronic materials (30%), exhibiting recyclability rates between 35% and 95%. The results indicate that the GA attains a 25% enhancement in recyclability, a 30% reduction in disassembly complexity, and a 20% decrease in carbon footprint relative to traditional approaches. The suggested method offers a versatile and scalable decision-making instrument for manufacturers, recyclers, and policymakers, enhancing a more sustainable resource recovery system.

关键词： Systematics Instruments Computational modeling Search methods Decision making Complexity theory Sustainable development Optimization Carbon footprint Genetic algorithms

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Mechanical performance of recycled PVC window frames: An experimental and numerical investigation

Hybrid Advances

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Hybrid Advances 2025年 9卷

作者： Ait Khouya, Oumaima Sebbar, EL Hassan Elfarissi, Latifa Laaroussi, Najma University Hassan II of Casablanca Laboratory of modeling and Simulation of Intelligent Industrial Systems ENSET Mohammedia Morocco Technical Center of Plastic and Rubber Casablanca Morocco Institute for Research in Solar Energy and New Energies-IRESEN Morocco University Mohammed V in Rabat Material Energy and Acoustics Team (MEAT) EST Salé Morocco

PVC window frames are commonly used in the construction industry due to their durability, low cost, and ease of maintenance. However, with growing environmental concerns and the shift towards a circular economy, replacing virgin PVC with recycled materials in such applications has become a critical area of research. The recycling process as well as the source of waste, highly impact the quality of the recycled materials which limits its use in high-quality products. This study investigates the mechanical characterization of window profiles made from recycled PVC, focusing on their ability to withstand structural loads. Given that window frames are exposed to wind forces and building loads, ensuring their mechanical resistance is essential. The bending and tensile behavior of recycled PVC specimens were tested experimentally and numerically to assess the structural performance of the material under different loading conditions. A comparison between the results of numerical finite element simulations and those of experiments has been carried out to validate the findings. The results show that recycled PVC offers adequate mechanical and thermal performance for use in the manufacture of window profiles. © 2025

关键词： Circular economy Plastic recycling PVC PVC profile Window frame

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A Comprehensive Review of Materials Used In Marine Engineering: Advances, Challenges and Practices 4

A Comprehensive Review of Materials Used In Marine Engineeri...

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4th International Conference on Innovative Research in Applied Science, Engineering and Technology, IRASET 2024

作者： Bouanani, Oumaima Ech-Chhibat, Moulay El Houssine Sandabad, Sara Enset Mohammedia Hassan Ii University Laboratory Of Modeling And Simulation Of Intelligent Industrial Systems Casablanca Morocco Enset Mohammedia Hassan Ii University Isem Laboratory Of Modeling And Simulation Of Intelligent Industrial Systems Casablanca Morocco

ISBN: (纸本)9798350309508

This article provides a comprehensive review of the current state of design and materials used in shipbuilding. It explores various types of vessels and innovative materials such as composites and steel employed in their construction. Additionally, the article examines different material tests discussed in the literature and their relevance in the maritime field. Ship corrosion is also addressed, with particular focus on mitigation strategies. Finally, the environmental impact of ships is discussed, highlighting implications and measures to minimize this impact. © 2024 IEEE.

关键词： Corrosion resistance

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Predicting the failure of plain dent pipeline subjected to cyclic loads using an artificial neural network 7

Predicting the failure of plain dent pipeline subjected to c...

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7th IEEE International Congress on Information Science and Technology, CiSt 2023

作者： Kiri, Yassine El Mighouar, Zakaria Zahiri, Laidi Mansouri, Khalifa Ouardi, Soufiane El Chaiti, Hammadi Hassan Ii University Laboratory of Modeling and Simulation of Intelligent Industrial Systems Enset Mohammedia Morocco

ISBN: (纸本)9781665461337

Pipelines are widely used to transport fluids over long distances. When a pipeline is subjected to variable internal pressure and external disturbances such as subsidence, structural damage caused by the presence of defects can intensify. Since 2010, the use of artificial intelligence has become a crucial means of solving complex problems, even for interpretation and decision-making using machine learning tools. The main aim of this paper is to use an artificial neural network to predict the failure of a cyclically loaded pipeline with a dent defect. A feedforward neural network has been created to predict the state of a dented pipeline using data from several experiments based on geometric and material properties and cyclic fluid pressure. It enables rapid detection of faults such as plain indentations for maintenance operatives, speeding up intervention time and reducing material and environmental damage. Two evaluation criteria were taken into account for the different models in order to select the optimum architecture in terms of accuracy. © 2023 IEEE.

关键词： Failure (mechanical)

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Characterization and evaluation of the treated water quality from the wastewater treatment plant of the Djelfa city 1

Characterization and evaluation of the treated water quality...

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1st International Conference on Renewable Solutions for Ecosystems: Towards a Sustainable Energy Transition, ICRSEtoSET 2023

作者： Karef, Salah Azlaoui, Mohamed Hameurlaine, Abdelhadi Fodili, Mokhtar University of Djelfa Laboratory of Modeling Optimization and Simulation of Real Complex Systems Djelfa Algeria University of Djelfa Laboratory of Applied Automation & Industrial Diagnostics Djelfa Algeria University of Djelfa Laboratory of Organic Chemistry and Natural Substances Djelfa Algeria

ISBN: (纸本)9798350346336

In the framework of the protection of the environment, we proceeded during the year 2016 (12 months), to the follow-up of variation of the wastewater pollution parameters at the inlet and at the outlet of the treatment plant of the Djelfa city, which operates by activated sludge, following the medium load *** physicochemical analyzes were carried out on the following parameters: pH, temperature, eclectic conductivity, turbidity, Total suspended solids, COD, BOD5, NH4+, NO3- and total phosphorus. At the end of these analyses, we obtained good elimination yield of 92% to 91% for TSS and 92% to 91% for BOD5. The COD recorded a reduction of 84% to 83%. Total phosphorus achieved a removal efficiency of 55% to 66%. For nitrogen, Ammonia experienced a 61% to 57% reduction from inlet to outlet of the plant. On the other hand, nitrates recorded an increase of 200% to 236%, due to *** quality of the treated water, for the majority of the parameters, complies with the standards required by Algerian regulations and those of the WHO. We can conclude that the treatment system adopted at the level of the WWTP of Djelfa is effective and justified its design and its objective of realization. © 2023 IEEE.

关键词： Phosphorus

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