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Tianshu Liu & Zemin Cai 
Inverse Problems in Global Flow Diagnostics [PDF ebook] 

สนับสนุน

This book describes unified image-based measurement methods (theories, numerical methods, and algorithms) to determine the important physical quantities of complex flows in engineering and natural systems, including velocity, pressure, temperature, heat transfer, and skin friction. It presents a systematical study of the inverse problems in global flow diagnostics in a unified framework of the variational formulations.  The authors further illustrate the main physical quantities in fluid mechanics, including velocity, pressure, skin friction and surface heat flux, extracted from flow visualization images obtained in experiments and observations.  The developed methods are applicable in various image-based flow measurements in diverse disciplines ranging from fluid mechanics/aerodynamics to plenary sciences. 

€171.19
วิธีการชำระเงิน

สารบัญ

Introduction.- Velocity from Flow Visualizations.- Skin Friction from Global Luminescent Oil-Film Visualizations.- Skin Friction from Surface Pressure Visualizations.- Skin Friction from Surface Temperature Visualizations.- Skin Friction from Surface Scalar Visualizations.- Skin Friction from Surface Optical Flow Pressure from Velocity.- Heat Flux from Surface Temperature Visualizations.- Analysis of Physics-Based Optical Flow.

เกี่ยวกับผู้แต่ง

Dr. Tianshu Liu is The John O. Hallquist Endowed Professor and The Presidential Innovation Professor in the Department of Mechanical and Aerospace Engineering, College of Engineering and Applied Sciences, Western Michigan University, Kalamazoo, Michigan, USA.
Dr. Zemin Cai is a Professor in the Department of Electronics, School of Engineering, Shantou University, Shantou, Guangdong, China.

ซื้อ eBook เล่มนี้และรับฟรีอีก 1 เล่ม!
ภาษา อังกฤษ ● รูป PDF ● หน้า 334 ● ISBN 9783031424748 ● ขนาดไฟล์ 18.6 MB ● อายุ 02-99 ปี ● สำนักพิมพ์ Springer Nature Switzerland ● เมือง Cham ● ประเทศ CH ● การตีพิมพ์ 2023 ● ที่สามารถดาวน์โหลดได้ 24 เดือน ● เงินตรา EUR ● ID 9157788 ● ป้องกันการคัดลอก โซเชียล DRM

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