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24 articles for “lifecycle assessment”
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Integrated Frameworks for Artifical Intelligence in Radioactive Waste Characterization and Nuclear Lifecycle Safety
Abstract: The management and characterization of radioactive waste represent a pivotal challenge for the global energy sector, requiring the convergence of advanced physics, material science, and computational intelligence. As the nuclear industry undergoes a paradigm shift toward decommissioning legacy facilities and establishing deep geological repositories, the limitations of traditional, manually-intensive waste management processes have become increasingly apparent. Rigid separation from the biosphere is required for radioactive waste, which is defined by …
Published in Journal of Nuclear Engineering & Technology · Vol. 16, Issue 2, 2026 Read article
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Reimagining Solid Waste Management in India: A case of Circular approach in C&D Waste Management
Abstract: Construction and demolition (C&D) waste, which accounts for an estimated 150–500 MT yearly and about 10–20% of the nation's total municipal solid waste (MSW) generation, is a significant management challenge for India. Accelerated urbanization, population increase, infrastructural expansion, and urban redevelopment initiatives are the main causes of this quickly expanding waste stream. Much of this waste is disposed of through uncontrolled dumping, encroachment on low-lying areas, and overcrowded landfills in …
Published in Journal of Construction Engineering, Technology & Management · Vol. 16, Issue 1, 2026 · pp. 1–10 Read article
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Incorporating Industrial Safety Management into Civil Engineering Works for Health and Environment
Abstract: Industrial safety management is an important tool for protecting workers, assets, and environment because it involves risk assessment, hazard control, emergency preparedness and other important practices that can enhance civil engineering construction. Civil engineering projects such as roads, bridges, dams, and water supply systems present complex occupational and environmental risks, from physical accidents on-site to ecological degradation. This paper critically examines the integration of industrial safety and management strategies into …
Published in Journal of Industrial Safety Engineering · Vol. 12, Issue 3, 2025 · pp. 25–41 Read article
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Multimodal Data Fusion with Hybrid Machine Learning for Enhanced Prediction of Li-Ion Battery Remaining Useful Life and State of Charge
Abstract: Lithium-ion battery materials used in modern energy storage systems are required to exhibit high reliability, safety, and long lifecycle performance under varying operational and environmental conditions. Accurate prediction of Remaining Useful Life (RUL) and State of Charge (SoC) is therefore essential for understanding material degradation behavior, improving manufacturing quality, and enabling effective lifecycle management. However, nonlinear electrochemical aging, load variability, and thermal uncertainty significantly complicate accurate estimation of these parameters. …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 4, Issue 1, 2026 · pp. 1–5 Read article