University of Florida Research Foundation, Incorporated

Woods Hole Oceanographic' Institution

Clarkson University

Special-lite, Inc.

Forrest James Masters

Christopher C Ferraro

Pedro L Fernandez-Caban

Brian M Phillips

Britt Raubenheimer

Wei-Ting Lu

Henry L Upjohn, Ii

James Paul Jesteadt

Yan Shen

Cedric Adam

Joseph Alex Esposito

Kenneth R Bowditch

Bob Nicholson

The present disclosure describes various embodiments of systems, apparatuses, and methods of monitoring wind and water properties. For one such weather monitoring system, a weather monitoring station comprises an upper mast section having an instrumentation package, wherein the instrumentation package includes an orientation sensor, communications circuitry, a wind velocity sensor, and a control unit that is configured to at least receive sensor data and transmit communication data via the communications circuitry. The weather monitoring station further includes at least one lower mast section that is coupled to the upper mast section, and an anchoring system that is coupled to the lower mast section, wherein the anchoring system includes at least one subsurface anchor for inserting into a ground surface within a littoral zone of a coastal area. Other systems, apparatuses, and methods are also provided.

In situ measurement station for monitoring wind and water properties in extreme hydrodynamic conditions

The present disclosure describes various embodiments of systems, apparatuses, and methods for large-scale processing of weather-related data. For one such system, the system comprises a database of weather-related data providing from at least one weather monitoring station and at least one processor for coordinating a data processing job for processing a set of input weather-related data from the database. Accordingly, the input data comprises sensor data from the at least one weather monitoring station positioned on an open shoreline during a hydrodynamic event, weather model data for the hydrodynamic event, and at least one of air-craft reconnaissance data or satellite reconnaissance data regarding the hydrodynamic event, wherein the at least one processor is configured to assimilate the input data and generate, using machine learning, an improved weather prediction model for the hydrodynamic event. Other systems, apparatuses, and methods are also provided.

The present disclosure describes various embodiments of systems, apparatuses, and methods for large-scale processing of weather-related data. For one such system, the system comprises a database of weather-related data providing from a plurality of weather monitoring stations and a plurality of interconnected processors for coordinating a data processing job for processing a set of input weather-related data from the database. Accordingly, the input data comprises sensor data from an array of weather monitoring stations positioned on an open shoreline during a hydrodynamic event, weather model data for the hydrodynamic event, and at least one of air-craft reconnaissance data or satellite reconnaissance data regarding the hydrodynamic event, wherein the plurality of interconnected processors are configured to assimilate the input data and generate, using machine learning, an improved weather prediction model for the hydrodynamic event. Other systems, apparatuses, and methods are also provided.

Various examples are provided for dynamic simulation of wind velocity and pressure. In one embodiment, among others, a dynamic wind simulator includes a fan and a fast-acting damper connected to an inlet of the fan. The fast-acting damper configured to modulate airflow provided by the fan at frequencies up to 10 Hz. In another embodiment, a system includes a fan and an air outlet path of the fan connected to a testing assembly configured to support a specimen for testing. An air inlet path of the fan includes a fast-acting damper configured to modulate airflow provided by the fan to the testing assembly at frequencies up to 10 Hz. The testing assembly may include a pressure chamber and/or a test section.

Dynamic wind velocity and pressure simulator

Growing community of inventors

Gainesville, FL, United States of America

Forrest James Masters