About this Research Topic
For air’s small viscosity, almost all winds appear turbulent by nature, particularly inside the troposphere where most manmade structures reside. Therefore, wind engineering is quintessentially the study of atmospheric turbulence and its effects on civil structures—an inherently cross-disciplinary discipline involving fluid mechanics, structural dynamics, atmospheric science, environmental science, etc. For centuries, fluid-structure interactions (FSI), and the associated issues of dimensionality, stochasticity, and nonlinearity, remained bottleneck conundrums of classical Newtonian physics, proposing great difficulties in Wind Engineering research, especially via traditional approaches.
Today, we are witnessing Data Science’s rise as the Fourth Paradigm of Scientific Discovery, which brought about vast new opportunities in research on FSI. For example, in the last decade or so, new wind tunnel or Computational Fluid Dynamics (CFD) technologies like Particle Image Velocimetry (PIV) and high Re Direct Numerical Simulations (DNS) have been developed to better detect and visualize winds. New algorithms like neural networks and reduced-order models have been invented to better analyze and dissect complex FSI dynamics. New insights into extreme winds like downbursts and tornados, as well as their effects on civil structures, have been disclosed for the first time. More impressively, new disciplines such as energy (e.g., wind turbines), epidemiology (e.g., air-borne disease transmission), environmental science (e.g., reactive air pollutant), and hazard prevention (i.e., typhoon/hurricane-resistant structures) have been added as the latest interdisciplinary dimensions of Wind Engineering.
At the cusp of Wind Engineering’s sixty-year milestone, advances deserve appraisal, but some existing questions also demand better answers. For example, in FSI terms, to what extent can natural winds be considered Gaussian? To what limits can wind-induced responses be considered quasi-static? How can extreme winds be better replicated to study their effects on structures? How can data-driven algorithms aid FSI analysis? Can FSI dynamics ever be accurately linearized, dimensionally reduced, or predicted? Can new data-driven approaches elucidate the excitation-response relationships in FSI? Answers to these questions will perhaps shape how Wind Engineering evolves in the future. Considering these issues, this dedicated Research Topic invites discoveries and discussions about all aspects of FSI in Wind Engineering.
The topics include, but are not limited, to the following:
• Generation/behavioral physics, phenomenology, characteristics, and patterns of any naturally-occurring wind;
• Design, construction, operation, maintenance, and health monitoring of all types of structures subjected to wind-induced load;
• Interactive physics of wind and structure, vehicles, or any manufactured matters;
• Transport physics of wind and biological agents, pollutants, or any natural or artificial air-borne matters;
• Experimental, numerical, or analytical techniques to better replicate, simulate, measure, or study wind-structure interactions;
• Wind-human interactions (i.e., wind environments, matter transport, heat ventilation, etc.);
• Discussions on better capture of wind for energy generation.
Today, we are witnessing Data Science’s rise as the Fourth Paradigm of Scientific Discovery, which brought about vast new opportunities in research on FSI. For example, in the last decade or so, new wind tunnel or Computational Fluid Dynamics (CFD) technologies like Particle Image Velocimetry (PIV) and high Re Direct Numerical Simulations (DNS) have been developed to better detect and visualize winds. New algorithms like neural networks and reduced-order models have been invented to better analyze and dissect complex FSI dynamics. New insights into extreme winds like downbursts and tornados, as well as their effects on civil structures, have been disclosed for the first time. More impressively, new disciplines such as energy (e.g., wind turbines), epidemiology (e.g., air-borne disease transmission), environmental science (e.g., reactive air pollutant), and hazard prevention (i.e., typhoon/hurricane-resistant structures) have been added as the latest interdisciplinary dimensions of Wind Engineering.
At the cusp of Wind Engineering’s sixty-year milestone, advances deserve appraisal, but some existing questions also demand better answers. For example, in FSI terms, to what extent can natural winds be considered Gaussian? To what limits can wind-induced responses be considered quasi-static? How can extreme winds be better replicated to study their effects on structures? How can data-driven algorithms aid FSI analysis? Can FSI dynamics ever be accurately linearized, dimensionally reduced, or predicted? Can new data-driven approaches elucidate the excitation-response relationships in FSI? Answers to these questions will perhaps shape how Wind Engineering evolves in the future. Considering these issues, this dedicated Research Topic invites discoveries and discussions about all aspects of FSI in Wind Engineering.
The topics include, but are not limited, to the following:
• Generation/behavioral physics, phenomenology, characteristics, and patterns of any naturally-occurring wind;
• Design, construction, operation, maintenance, and health monitoring of all types of structures subjected to wind-induced load;
• Interactive physics of wind and structure, vehicles, or any manufactured matters;
• Transport physics of wind and biological agents, pollutants, or any natural or artificial air-borne matters;
• Experimental, numerical, or analytical techniques to better replicate, simulate, measure, or study wind-structure interactions;
• Wind-human interactions (i.e., wind environments, matter transport, heat ventilation, etc.);
• Discussions on better capture of wind for energy generation.
Keywords: Structure Dynamics, Wind tunnel, CFD, hazard prevention, structure safety, fluid dynamics
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