Ernesto Benini – författare

This book aims to provide practical aspects of, and an introduction to, the applications of various technological advancement tools, such as AI, machine learning to design, big data, cloud computing, and IoT, to model, characterize, optimize, forecast, and do performance prediction of renewable energy exploitation. It further discusses new avenues for energy sources such as hydrogen energy generation and energy storage technologies including existing policies and case studies for a better understanding of renewable energy generation.Features:Covers technologies considered to explore, predict, and perform operation and maintenance of renewable energy sourcesAids in the design and use of renewable energy sources, including the application of artificial intelligence in a real-time environmentIncludes IoT, cloud computing, big data, smart grid, and different optimization techniques for resource forecasting, installation, operation, and optimization of energyDiscusses the principle of integration/hybridization of renewable energy sources along with their optimization based on energy requirementsReviews the concepts and challenges involved in the implementation of smart gridsThis book is aimed at researchers and graduate students in renewable energy engineering, computer and mechanical engineering, novel technologies, and intelligent systems.

This book aims to provide practical aspects of, and an introduction to, the applications of various technological advancement tools, such as AI, machine learning to design, big data, cloud computing, and IoT, to model, characterize, optimize, forecast, and do performance prediction of renewable energy exploitation. It further discusses new avenues for energy sources such as hydrogen energy generation and energy storage technologies including existing policies and case studies for a better understanding of renewable energy generation.Features:Covers technologies considered to explore, predict, and perform operation and maintenance of renewable energy sourcesAids in the design and use of renewable energy sources, including the application of artificial intelligence in a real-time environmentIncludes IoT, cloud computing, big data, smart grid, and different optimization techniques for resource forecasting, installation, operation, and optimization of energyDiscusses the principle of integration/hybridization of renewable energy sources along with their optimization based on energy requirementsReviews the concepts and challenges involved in the implementation of smart gridsThis book is aimed at researchers and graduate students in renewable energy engineering, computer and mechanical engineering, novel technologies, and intelligent systems.

Fundamentals of Turbomachinery simplifies complex turbomachinery concepts, helping engineering students understand the basics step by step to prepare for more advanced studies and real-world applications. It provides the theoretical background needed to explain the principles underlying turbomachinery behavior with a strong emphasis on a solid mathematical foundation.Designed to guide readers through an understanding of machines in terms of increasing complexity, this textbook focuses on core principles instead of advanced approximations or computational tools. It covers dimensional analysis and pump systems before progressing into axial compressors, axial turbines, centrifugal compressors, and centripetal turbines. The chapters transition from theoretical and mathematical concepts to practical applications and feature numerous end-of-chapter problems and examples.This book is intended for senior undergraduate engineering students taking turbomachinery and fluid mechanics courses.Instructors will be able to utilize a Solutions Manual and Figure Slides for their course.

Design Optimization of Fluid Machinery: Applying Computational Fluid Dynamics and Numerical Optimization Drawing on extensive research and experience, this timely reference brings together numerical optimization methods for fluid machinery and its key industrial applications. It logically lays out the context required to understand computational fluid dynamics by introducing the basics of fluid mechanics, fluid machines and their components. Readers are then introduced to single and multi-objective optimization methods, automated optimization, surrogate models, and evolutionary algorithms. Finally, design approaches and applications in the areas of pumps, turbines, compressors, and other fluid machinery systems are clearly explained, with special emphasis on renewable energy systems. Written by an international team of leading experts in the fieldBrings together optimization methods using computational fluid dynamics for fluid machinery in one handy referenceFeatures industrially important applications, with key sections on renewable energy systemsDesign Optimization of Fluid Machinery is an essential guide for graduate students, researchers, engineers working in fluid machinery and its optimization methods. It is a comprehensive reference text for advanced students in mechanical engineering and related fields of fluid dynamics and aerospace engineering.