Quan Wang – författare

Re-exploration Programs for Petroleum-Rich Sags in Rift Basins covers the geological characteristics and potential of oil-rich depressions in a rifted basin. It describes up-to-date research and technology, detailing the current status of exploration. The overall aim of the book is to guide a new round of hydrocarbon exploration of petroleum-rich depressions, contributing to breakthroughs in re-exploration and a substantial increase in reserves. Chapters discuss the reservoir forming theory of oil-rich depressions, characters of hydrocarbon migration and accumulation in a weak structure slope, key elements of reservoir forming of deep buried hills and inner curtains, and more.

Other topics covered include complex subtle reservoir recognition techniques, deep layer and buried hill high speed drill technology, recognition of buried hill reservoir and hydrocarbon, high efficiency enhanced oil recovery, and finally, methods of secondary exploration of oil-rich depressions and the development of a workflow to guide research and exploration.

Wind Turbine Airfoils and Blades introduces new ideas in the design of wind turbine airfoils and blades based on functional integral theory and the finite element method, accompanied by results from wind tunnel testing. The authors also discuss the optimization of wind turbine blades as well as results from aerodynamic analysis. This book is suitable for researchers and engineers in aeronautics and can be used as a textbook for graduate students.

Wind Turbine Airfoils and Blades introduces new ideas in the design of wind turbine airfoils and blades based on functional integral theory and the finite element method, accompanied by results from wind tunnel testing. The authors also discuss the optimization of wind turbine blades as well as results from aerodynamic analysis. This book is suitable for researchers and engineers in aeronautics and can be used as a textbook for graduate students.

It has been suggested that local parity violation (LPV) in Quantum Chromodynamics (QCD) would lead to charge separation of quarks by the Chiral Magnetic Effect (CME) in heavy ion collisions. Charge Multiplicity Asymmetry Correlation Study Searching for Local Parity Violation at RHIC for STAR Collaboration presents the detailed study of charge separation with respect to the event plane.

Results on charge multiplicity asymmetry in Au+Au and d+Au collisions at 200 GeV by the STAR experiment are reported. It was found that the correlation results could not be explained by CME alone. Additionally, the charge separation signal as a function of the measured azimuthal angle range as well as the event-by-event anisotropy parameter are studied. These results indicate that the charge separation effect appears to be in-plane rather than out-of-plane. It is discovered that the charge separation effect is proportional to the event-by-event azimuthal anisotropy and consistent with zero in events with zero azimuthal anisotropy.

These studies suggest that the charge separation effect, within the statistical error, may be a net effect of event anisotropy and correlated particle production. A potential upper limit on the CME is also presented through this data.

The 27 revised full papers and 2 revised short papers presented were carefully reviewed and selected from 101 submissions. The papers cover wide research fields including the knowledge graph, information extraction, knowledge representation and reasoning, linked data.

This book constitutes the refereed proceedings of the The 6th Conference on Intelligent Networked Things on Intelligent Networked Things, CINT 2024, held in Xi''an, China, in May 18, 2024. 

The 51 full papers presented were carefully reviewed and selected from 151 submissions. The conference papers are organized in topical sections on:

Part I - Theories and Mathematical Methods for Intelligent Networked Things; Modeling and Simulation in Intelligent Networked Things.

Part II - Artificial Intelligence for Intelligent Networked Things; Optimization and Decision in Intelligent Networked Things.