Danial Jahed Armaghani – författare

The design of structures and infrastructure facilities has typically assumed a future climate that is much the same as today’s. However, a changing climate and the resulting more extreme weather events mean those climate bands are becoming outdated, leaving infrastructure operating outside or at the limit of its tolerance levels.With its evaluation of a host of assets in the built environment, Climate Change Effects on Infrastructure: Advanced Tools for Monitoring, Mitigation, and Lifecycle Optimization instructs readers how to assess and predict structural vulnerabilities resulting from climate change as well as ensuing hazard patterns using mathematical tools and data-driven models. The carefully compiled contributions also comprehensively survey the latest technological developments and the most useful approaches to counteract and/or prevent damage and connected socio-economic risks.The volume proves to be an even more invaluable resource thanks to its real-world application examples that spotlight the urgency of further investigations into the implementation of cost-effective and sustainable adaptive measures that can enhance or extend the reliable performance, durability, and efficiency of structures and infrastructure systems throughout their entire lifecycle.Reviews advanced computational models, simulations, and data analytics techniques for determining the effects of climate change on infrastructure.Describes advanced methods to enhance infrastructure resilience and offset or prevent the adverse impacts of climate change.Features case studies and applied examples for different structure types and infrastructure systems from a variety of regions and assorted scenarios.

Advancements in Underground Infrastructures presents the advanced modelling tools and experimental techniques applied in underground infrastructure development. It examines the usage of mathematical tools, experimental techniques, and data-driven models, as well as the latest technological advancements in underground engineering used to enhance the safety and stability of underground structures. It also addresses the application of the circular economy model in underground engineering.Provides modelling theories in an easy-to-read format verified by on-site models for various regions and scenariosPresents applications of soft computing tools and techniques in underground engineeringIncludes practical examples and case studiesColour versions of the figures in this book can be found at www.routledge.com/9781032373379.

Advancements in Underground Infrastructures presents the advanced modelling tools and experimental techniques applied in underground infrastructure development. It examines the usage of mathematical tools, experimental techniques, and data-driven models, as well as the latest technological advancements in underground engineering used to enhance the safety and stability of underground structures. It also addresses the application of the circular economy model in underground engineering.Provides modelling theories in an easy-to-read format verified by on-site models for various regions and scenariosPresents applications of soft computing tools and techniques in underground engineeringIncludes practical examples and case studiesColour versions of the figures in this book can be found at www.routledge.com/9781032373379.

This book covers the tunnel boring machine (TBM) performance classifications, empirical models, statistical and intelligent-based techniques which have been applied and introduced by the researchers in this field. The introduced models are accurate enough and they can be used for prediction of TBM performance in practice before designing TBMs.

This book gives a rigorous and up-to-date study of the various AI and machine learning algorithms for resolving environmental challenges associated with blasting. A small amount of explosive energy is only used during blasting to fracture rock in order to achieve the appropriate fragmentation, throw, and development of muck pile.

Recent studies highlight the application of artificial intelligence, machine learning, and simulation techniques in engineering. This book covers the successful implementation of different intelligent techniques in various areas of engineering focusing on common areas between mechatronics and civil engineering.

Recent studies highlight the application of artificial intelligence, machine learning, and simulation techniques in engineering. This book covers the successful implementation of different intelligent techniques in various areas of engineering focusing on common areas between mechatronics and civil engineering.

This book demonstrates innovative approaches in the application of computational intelligence. The initial chapters discuss the application of AI to analyze physical systems, in particular contemporary neural networks for rapid and accurate seismic analysis of critical infrastructure. It also discusses advanced metaheuristic and hybrid AI approaches that afford robust, non-invasive evaluations of geological and rock-mass properties, replacing the expensive and time-consuming traditional methods. The subsequent chapters expand the scope to include strategic and operational intelligence dimensions, where the use of generative AI aims at enhancing the security and functionality of IoT ecosystems, and where the seamless interplay of Natural Language Processing and IoT technology enables more human-centred control of systems. It also describes Edge AI, elaborating the on-device processing capabilities that enable fast, secure, real-time decision-making.

The introduction of AI and ML technologies has brought new changes to the engineering profession. This book presents the theory and practical solutions backed with real results. It also explains in detail the uses of Machine Learning methods, Gene Expression Programming, Extreme Gradient Boosting, and Deep Neural Networks in predicting parameters that are critical in understanding soil behavior, foundation settlements, material behavior, resource consumption, and beyond. One focal point is the shift from opaque models to transparent, accountable AI. The integration of AI methods is elucidated to clarify decisions made by predictive models and instill trust in the predictive systems. Additionally, the book addresses the issue of sustainability by demonstrating how AI can refine the utilization of industrial by-products such as fly ash and marble slurry in the construction sector and improve the efficiency of public transportation systems.