Alan Pope – författare

A brand-new edition of the classic guide on low-speed wind tunnel testing While great advances in theoretical and computational methods have been made in recent years, low-speed wind tunnel testing remains essential for obtaining the full range of data needed to guide detailed design decisions for many practical engineering problems. This long-awaited Third Edition of William H. Rae, Jr.'s landmark reference brings together essential information on all aspects of low-speed wind tunnel design, analysis, testing, and instrumentation in one easy-to-use resource. Written by authors who are among the most respected wind tunnel engineers in the world, this edition has been updated to address current topics and applications, and includes coverage of digital electronics, new instrumentation, video and photographic methods, pressure-sensitive paint, and liquid crystal-based measurement methods. The book is organized for quick access to topics of interest, and examines basic test techniques and objectives of modeling and testing aircraft designs in low-speed wind tunnels, as well as applications to fluid motion analysis, automobiles, marine vessels, buildings, bridges, and other structures subject to wind loading. Supplemented with real-world examples throughout, Low-Speed Wind Tunnel Testing, Third Edition is an indispensable resource for aerospace engineering students and professionals, engineers and researchers in the automotive industries, wind tunnel designers, architects, and others who need to get the most from low-speed wind tunnel technology and experiments in their work.

This book constitutes the proceedings of the Third International Conference on Physiological Computing Systems, PhyCS 2016, held in Lisbon, Portugal, in July 2016.The 12 papers presented in this volume were carefully reviewed and selected from numerous submissions. They contribute to the understanding of relevant trends of current research on physiological computing systems, including brain-computer interfaces, virtual reality, psychophysiological load assessment in unconstrained scenarios, body tracking and movement pattern recognition, emotion recognition, machine learning applied to diabetes and hypertension, tangible biofeedback technologies, multimodal sensor data fusion, and deep learning for hand gesture recognition.