Artificial Intelligence And Data Driven Optimization Of Internal Combustion Engines
Download Artificial Intelligence And Data Driven Optimization Of Internal Combustion Engines PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Artificial Intelligence And Data Driven Optimization Of Internal Combustion Engines book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Artificial Intelligence and Data Driven Optimization of Internal Combustion Engines
Artificial Intelligence and Data Driven Optimization of Internal Combustion Engines summarizes recent developments in Artificial Intelligence (AI)/Machine Learning (ML) and data driven optimization and calibration techniques for internal combustion engines. The book covers AI/ML and data driven methods to optimize fuel formulations and engine combustion systems, predict cycle to cycle variations, and optimize after-treatment systems and experimental engine calibration. It contains all the details of the latest optimization techniques along with their application to ICE, making it ideal for automotive engineers, mechanical engineers, OEMs and R&D centers involved in engine design. - Provides AI/ML and data driven optimization techniques in combination with Computational Fluid Dynamics (CFD) to optimize engine combustion systems - Features a comprehensive overview of how AI/ML techniques are used in conjunction with simulations and experiments - Discusses data driven optimization techniques for fuel formulations and vehicle control calibration
Diesel Engines - Current Challenges and Future Perspectives
This book discusses the current technology and future status of diesel engines. While gasoline engines are preferred for speed and jet engines, diesel engines are widely used in vehicles and machinery that require torque, such as ships, trains, tanks, unmanned ariel vehicles (UAVs), and heavy-duty vehicles. Some recent research on global climate change has focused on obtaining zero carbon, zero emissions, and decarbonization via clean combustion technologies. For this reason, restrictive emission regulations have forced engine manufacturers and research centers to turn to different technologies to achieve clean combustion in diesel engines. This book focuses on different combustion technologies, from artificial intelligence applications in diesel engines to alternative fuels. It discusses the roles of artificial intelligence in the design of diesel engines, the use of different fuels in diesel engines, and the effects of these on the performance and emission values of diesel engines. Solving the challenge of hydrogen storage in hydrogen-fed diesel engines will open a new era for internal combustion engines. In particular, the use of hydrogen fuel produced by the reaction of chemical ingredients with water in diesel engine cycles will have a significant impact on the industry. This book, which brings together the latest studies on clean combustion technologies, is an interesting resource for both industry and research centers.
Artificial Intelligence Applications and Innovations
Author: Ilias Maglogiannis
language: en
Publisher: Springer Nature
Release Date: 2023-05-31
This two-volume set of IFIP-AICT 675 and 676 constitutes the refereed proceedings of the 19th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2023, held in León, Spain, during June 14–17, 2023. This event was held in hybrid mode. The 75 regular papers and 17 short papers presented in this two-volume set were carefully reviewed and selected from 185 submissions. The papers cover the following topics: Deep Learning (Reinforcement/Recurrent Gradient Boosting/Adversarial); Agents/Case Based Reasoning/Sentiment Analysis; Biomedical - Image Analysis; CNN - Convolutional Neural Networks YOLO CNN; Cyber Security/Anomaly Detection; Explainable AI/Social Impact of AI; Graph Neural Networks/Constraint Programming; IoT/Fuzzy Modeling/Augmented Reality; LEARNING (Active-AutoEncoders-Federated); Machine Learning; Natural Language; Optimization-Genetic Programming; Robotics; Spiking NN; and Text Mining /Transfer Learning.