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  • Open Access

    ARTICLE

    Impact on Mechanical Properties of Surface Treated Coconut Leaf Sheath Fiber/Sic Nano Particles Reinforced Phenol-formaldehyde Polymer Composites

    B. BRAILSON MANSINGH1, K. L. NARASIMHAMU2, K. C. VARAPRASAD3, J. S. BINOJ4,*, A. RADHAKRISHNAN5, ALAMRY ALI6

    Journal of Polymer Materials, Vol.40, No.1-2, pp. 71-82, 2023, DOI:10.32381/JPM.2023.40.1-2.6

    Abstract Several agro-wastes are rich in natural fibers and finds scope to be used as reinforcement in composite industry. These natural fibers have some advantages over man-made fibers, including low cost, light weight, renewable nature, high specific strength and modulus, and availability in various forms worldwide. In this paper, the effect of surface modification of leaf sheath coconut fiber (LSF) (an agro-waste) reinforced in phenol formaldehyde matrix composites with silicon carbide (SiC) nano particles as filler material were investigated for its mechanical characteristics. The investigation portrays that coconut LSF (CLSF) modified with potassium permanganate reinforced polymer composite with SiC nano particles… More >

  • Open Access

    REVIEW

    The Application of Solid Waste in Thermal Insulation Materials: A Review

    Ming Liu1, Pinghua Zhu2,*, Xiancui Yan2, Haichao Li2, Xintong Chen2

    Journal of Renewable Materials, Vol.12, No.2, pp. 329-347, 2024, DOI:10.32604/jrm.2023.045381

    Abstract As socioeconomic development continues, the issue of building energy consumption has attracted significant attention, and improving the thermal insulation performance of buildings has become a crucial strategic measure. Simultaneously, the application of solid waste in insulation materials has also become a hot topic. This paper reviews the sources and classifications of solid waste, focusing on research progress in its application as insulation materials in the domains of daily life, agriculture, and industry. The research shows that incorporating household solid waste materials, such as waste glass, paper, and clothing scraps into cementitious thermal insulation can significantly reduce the thermal conductivity of… More >

  • Open Access

    ARTICLE

    An Evidence-Based CoCoSo Framework with Double Hierarchy Linguistic Data for Viable Selection of Hydrogen Storage Methods

    Raghunathan Krishankumar1, Dhruva Sundararajan2, K. S. Ravichandran2, Edmundas Kazimieras Zavadskas3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2845-2872, 2024, DOI:10.32604/cmes.2023.029438

    Abstract Hydrogen is the new age alternative energy source to combat energy demand and climate change. Storage of hydrogen is vital for a nation’s growth. Works of literature provide different methods for storing the produced hydrogen, and the rational selection of a viable method is crucial for promoting sustainability and green practices. Typically, hydrogen storage is associated with diverse sustainable and circular economy (SCE) criteria. As a result, the authors consider the situation a multi-criteria decision-making (MCDM) problem. Studies infer that previous models for hydrogen storage method (HSM) selection (i) do not consider preferences in the natural language form; (ii) weights… More >

  • Open Access

    ARTICLE

    Suitability and Sustainability of Rainwater Quality Monitoring System in Cistern for Domestic Use

    Kenedy A. Greyson*

    Journal on Internet of Things, Vol.5, pp. 1-11, 2023, DOI:10.32604/jiot.2023.040255

    Abstract Rainwater harvesting (RWH) systems have been the source of domestic water for many years and still becoming essential in many communities of developing countries. However, due to various reasons, there are several sources of contamination in the rainwater cistern systems. Dissolved chemicals from the roofing, storage, and conveyance materials, together with the suspended particulate matter from the airborne, are examples of water contamination. In this work, the water quality monitoring system has been designed and implemented. Chemical and physical parameters of water samples were collected from three locations using a data acquisition (DAQ) system and rainwater quality was analyzed using… More >

  • Open Access

    ARTICLE

    Predictive Multimodal Deep Learning-Based Sustainable Renewable and Non-Renewable Energy Utilization

    Abdelwahed Motwakel1,*, Marwa Obayya2, Nadhem Nemri3, Khaled Tarmissi4, Heba Mohsen5, Mohammed Rizwanulla6, Ishfaq Yaseen6, Abu Sarwar Zamani6

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 1267-1281, 2023, DOI:10.32604/csse.2023.037735

    Abstract Recently, renewable energy (RE) has become popular due to its benefits, such as being inexpensive, low-carbon, ecologically friendly, steady, and reliable. The RE sources are gradually combined with non-renewable energy (NRE) sources into electric grids to satisfy energy demands. Since energy utilization is highly related to national energy policy, energy prediction using artificial intelligence (AI) and deep learning (DL) based models can be employed for energy prediction on RE and NRE power resources. Predicting energy consumption of RE and NRE sources using effective models becomes necessary. With this motivation, this study presents a new multimodal fusion-based predictive tool for energy… More >

  • Open Access

    ARTICLE

    Forecasting the Municipal Solid Waste Using GSO-XGBoost Model

    Vaishnavi Jayaraman1, Arun Raj Lakshminarayanan1,*, Saravanan Parthasarathy1, A. Suganthy2

    Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 301-320, 2023, DOI:10.32604/iasc.2023.037823

    Abstract Waste production rises in tandem with population growth and increased utilization. The indecorous disposal of waste paves the way for huge disaster named as climate change. The National Environment Agency (NEA) of Singapore oversees the sustainable management of waste across the country. The three main contributors to the solid waste of Singapore are paper and cardboard (P&C), plastic, and food scraps. Besides, they have a negligible rate of recycling. In this study, Machine Learning techniques were utilized to forecast the amount of garbage also known as waste audits. The waste audit would aid the authorities to plan their waste infrastructure.… More >

  • Open Access

    ARTICLE

    Modelling Dry Port Systems in the Framework of Inland Waterway Container Terminals

    Milovan Kovač1, Snežana Tadić1, Mladen Krstić1,*, Violeta Roso2

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 1019-1046, 2023, DOI:10.32604/cmes.2023.027909

    Abstract Overcoming the global sustainability challenges of logistics requires applying solutions that minimize the negative effects of logistics activities. The most efficient way of doing so is through intermodal transportation (IT). Current IT systems rely mostly on road, rail, and sea transport, not inland waterway transport. Developing dry port (DP) terminals has been proven as a sustainable means of promoting and utilizing IT in the hinterland of seaport container terminals. Conventional DP systems consolidate container flows from/to seaports and integrate road and rail transportation modes in the hinterland which improves the sustainability of the whole logistics system. In this article, to… More >

  • Open Access

    ARTICLE

    Solar Radiation Prediction Using Satin Bowerbird Optimization with Modified Deep Learning

    Sheren Sadiq Hasan1, Zainab Salih Agee2, Bareen Shamsaldeen Tahir3, Subhi R. M. Zeebaree4,*

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3225-3238, 2023, DOI:10.32604/csse.2023.037434

    Abstract Solar energy will be a great alternative to fossil fuels since it is clean and renewable. The photovoltaic (PV) mechanism produces sunbeams’ green energy without noise or pollution. The PV mechanism seems simple, seldom malfunctioning, and easy to install. PV energy productivity significantly contributes to smart grids through many small PV mechanisms. Precise solar radiation (SR) prediction could substantially reduce the impact and cost relating to the advancement of solar energy. In recent times, several SR predictive mechanism was formulated, namely artificial neural network (ANN), autoregressive moving average, and support vector machine (SVM). Therefore, this article develops an optimal Modified… More >

  • Open Access

    ARTICLE

    Sustainability Assessment of Protein-Soil Composite Materials for Limited Resource Environments

    Henning Roedel1, Isamar Rosa Plata1, Michael Lepech1,*, David Loftus2

    Journal of Renewable Materials, Vol.3, No.3, pp. 183-194, 2015, DOI:10.7569/JRM.2015.634107

    Abstract This article presents the sustainability assessment of a novel biocomposite material that is under investigation by NASA for use in construction in limited resource environments. The composite consists of soil particles solidified by a protein binding agent. Preliminary compressive strength data suggests the biocomposite could be used for numerous construction applications. To assess the biocomposite’s potential for use in sustainable construction, a comparative process-based life cycle assessment between biocomposite and concrete pavers was performed to analyze the life cycle primary energy and IMPACT 2002+ points of both types of pavers. Results show that the concrete pavers outperform the biocomposite pavers… More >

  • Open Access

    ARTICLE

    Big Data Analytics with Artificial Intelligence Enabled Environmental Air Pollution Monitoring Framework

    Manar Ahmed Hamza1,*, Hadil Shaiba2, Radwa Marzouk3, Ahmad Alhindi4, Mashael M. Asiri5, Ishfaq Yaseen1, Abdelwahed Motwakel1, Mohammed Rizwanullah1

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3235-3250, 2022, DOI:10.32604/cmc.2022.029604

    Abstract Environmental sustainability is the rate of renewable resource harvesting, pollution control, and non-renewable resource exhaustion. Air pollution is a significant issue confronted by the environment particularly by highly populated countries like India. Due to increased population, the number of vehicles also continues to increase. Each vehicle has its individual emission rate; however, the issue arises when the emission rate crosses the standard value and the quality of the air gets degraded. Owing to the technological advances in machine learning (ML), it is possible to develop prediction approaches to monitor and control pollution using real time data. With the development of… More >

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