Numerical Prediction Of Flow Heat Transfer Turbulence And Combustion

Numerical Prediction of Flow, Heat Transfer, Turbulence and Combustion

Numerical Prediction of Flow, Heat Transfer, Turbulence and Combustion: Selected Works of Professor D. Brian Spalding focuses on the many contributions of Professor Spalding on thermodynamics. This compilation of his works is done to honor the professor on the occasion of his 60th birthday. Relatively, the works contained in this book are selected to highlight the genius of Professor Spalding in this field of interest. The book presents various research on combustion, heat transfer, turbulence, and flows. His thinking on separated flows paved the way for the multi-dimensional modeling of turbulence. Arguments on the universality of the models of turbulence and the problems that are associated with combustion engineering are clarified. The text notes the importance of combustion science as well as the problems associated with it. Mathematical computations are also presented in determining turbulent flows in different environments, including on curved pipes, curved ducts, and rotating ducts. These calculations are presented to further strengthen the claims of Professor Spalding in this discipline. The book is a great find for those who are interested in studying thermodynamics.

Numerical Prediction of Flow, Heat Transfer Turbulence Combustion: Selected Works

Cognitive Computing for Smart Automotive Transportation

This reference book explores the integration of cognitive computing technologies in the automotive industry to enhance smart transportation systems. It focuses on how AI, machine learning, and data analytics can improve vehicle automation, safety, and efficiency. Automation can support driverless vehicle transportation and bridge the gap between manual control and fully automated navigation systems. The text introduces a discussion on numerous applications of cognitive computing in smart transportation, motion planning, situation awareness, dynamic driving, adaptive behavior, human intent measurement, and predictive analysis. Key Features: • Discusses basic concepts and architecture of cognitive computing for vehicular systems. • Presents technologies to measure human intent for vehicle safety, including emergency management systems (EMS). • Covers the perception and localization processes in autonomous driving through LiDAR, GPS, and Stereo vision data with critical decision‐making and simulation results. • Elucidates the application of motion planning for smart transportation. • Covers visual perception technologies for advanced driver assistance systems (ADAS) through deep learning. The text is primarily written for graduate students, academic researchers, and professionals in the fields of computer science, electrical engineering, automotive engineering, and civil engineering.