This study is about the data analysis of wind speed on sea surface, water temperature, atmospheric temperature, and sea waves observations from four buoy stations (Hua-Lian , Hsin-Chu , E-Luuan-Bi and Kin-Men) that belong to Central Weather Bureau Republic of China and Water Resources Agency, and related researches. The period of this study is in winter and summer from 2001 to 2003. Because of the shelter effect from building or hillocks in land, the wind speed on land is abated and not consistent with that on sea. Comparing data form two island stations ( Dongjido and Lanyu) and four buoy stations, the winds around Taiwan are almost the same. That means the monsoon controls the wind direction in summers and winters. Comparing the quantitative results from different wind speed areas in same period of time, the continuity of sea wind is better than that of land wind, especially best in west Taiwan. Also comparing the changes of wind speed in different atmospheric stability layers, wind is stronger in neural than others. Wind speed distribution also showed wind speeds increased when it is far from land, and sea breeze happened near land within 1-2 kilometer. Sea temperature and wind speed are the factors affecting stability. The diurnal variation of air temperature is greater than that of sea and diurnal variation of sea is more significant during winter. Especially along coastal in Eastern Taiwan, the temperature difference between sea and atmosphere could be greater than 10 ¢J, moreover the wind speed on sea surface in Hua-Lian is slow. Therefore, it caused more unstable on sea surface in Hua-Lian. waves could be classified into two types by wave age: swell and wind sea. Swell means because of passing long fetch, the weave height and wave period are saturated and no longer develop. It can¡¦t reveal the effects of sea wind on waves. Therefore, if swell is the major composition of waves, the inaccuracy of calculated stress would be large. On the contrary, when wind sea is the major composition of waves, roughness could be calculated by wave steepness. While analyzing coefficient of momentum flux on sea surface near Taiwan, gust factor under neutral and unstable conditions had different. Gust factor would change with wind speed under neutral condition, but change with stability under unstable condition. In neutral condition, wind speed and drag coefficient are direct proportion and then correlation among p of power law of wind profile, turbulence intensity and gust factor under neutral condition and strong wind are similar, the value close to 0.1.

The increasing nationwide interest in intelligent transportation systems (ITS) and the need for more efficient transportation have led to the expanding use of variable message sign (VMS) technology. VMS panels are substantially heavier than flat panel aluminum signs and have a larger depth (dimension parallel to the direction of traffic). The additional weight and depth can have a significant effect on the aerodynamic forces and inertial loads transmitted to the support structure. The wind induced drag forces and the response of VMS structures is not well understood. Minimum design requirements for VMS structures are contained in the American Association of State Highway Transportation Officials Standard Specification for Structural Support for Highway Signs, Luminaires, and Traffic Signals (AASHTO Specification). However the Specification does not take into account the prismatic geometry of VMS and the complex interaction of the applied aerodynamic forces to the support structure. In view of the lack of code guidance and the limited number research performed so far, targeted experimentation and large scale testing was conducted at the Florida International University (FIU) Wall of Wind (WOW) to provide reliable drag coefficients and investigate the aerodynamic instability of VMS. A comprehensive range of VMS geometries was tested in turbulence representative of the high frequency end of the spectrum in a simulated suburban atmospheric boundary layer. The mean normal, lateral and vertical lift force coefficients, in addition to the twisting moment coefficient and eccentricity ratio, were determined using the measured data for each model. Wind tunnel testing confirmed that drag on a prismatic VMS is smaller than the 1.7 suggested value in the current AASHTO Specification (2013). An alternative to the AASHTO Specification code value is presented in the form of a design matrix. Testing and analysis also indicated that vortex shedding oscillations and galloping instability could be significant for VMS signs with a large depth ratio attached to a structure with a low natural frequency. The effect of corner modification was investigated by testing models with chamfered and rounded corners. Results demonstrated an additional decrease in the drag coefficient but a possible Reynolds number dependency for the rounded corner configuration.

Hurricanes are one of the deadliest and costliest natural hazards affecting the Gulf coast and Atlantic coast areas of the United States. An effective way to minimize hurricane damage is to strengthen structures and buildings. The investigation of surface level hurricane wind behavior and the resultant wind loads on structures is aimed at providing structural engineers with information on hurricane wind characteristics required for the design of safe structures. Information on mean wind profiles, gust factors, turbulence intensity, integral scale, and turbulence spectra and co-spectra is essential for developing realistic models of wind pressure and wind loads on structures. The research performed for this study was motivated by the fact that considerably fewer data and validated models are available for tropical than for extratropical storms. Using the surface wind measurements collected by the Florida Coastal Monitoring Program (FCMP) during hurricane passages over coastal areas, this study presents comparisons of surface roughness length estimates obtained by using several estimation methods, and estimates of the mean wind and turbulence structure of hurricane winds over coastal areas under neutral stratification conditions. In addition, a program has been developed and tested to systematically analyze Wall of Wind (WoW) data, that will make it possible to perform analyses of baseline characteristics of flow obtained in the WoW. This program can be used in future research to compare WoW data with FCMP data, as gust and turbulence generator systems and other flow management devices will be used to create WoW flows that match as closely as possible real hurricane wind conditions. Hurricanes are defined as tropical cyclones for which the maximum 1-minute sustained surface wind speeds exceed 74 mph. FCMP data include data for tropical cyclones with lower sustained speeds. However, for the winds analyzed in this study the speeds were sufficiently high to assure that neutral stratification prevailed. This assures that the characteristics of those winds are similar to those prevailing in hurricanes. For this reason in this study the terms tropical cyclones and hurricanes are used interchangeably.

<p dir="ltr">Methodologies for optimizing UAVs' control for varied environmental conditions have become crucial in the recent development for UAV control sector, yet they are lacking. This research focuses on the dynamism of the Gazebo simulator and PX4 Autopilot flight controller, frequently referenced in academic sectors for their versatility in generating close-to-reality digital environments. This thesis proposed an integrated simulation system that ensures realistic wind and gust interactions in the digital world and efficient data extraction by employing an industrial standard control communication protocol called MAVLink with the also the industry standard ground control software QGroundControl, using real and historical weather information from NOAA database. This study also looks into the potential of reinforcement learning, namely the DDPG algorithm, in determining optimal UAV safety distance, trajectory prediction, and mission planning under wind disruption. The overall goal is to enhance UAV stability and safety in various wind-disturbed conditions. Mainly focusing on minimizing potential collision risks in areas such as streets, valleys, tunnels, or really anywhere has winds and obstacles. The ROS network further enhanced these components, streamlining UAV response analysis in simulated conditions. This research presents a machine-learning approach to UAV flight safety and efficiency in dynamic environments by synthesizing an integrated simulation system with reinforcement learning. And the results model has a high accuracy, reaching 91%, 92%, and 97% accuracy on average in prediction of maximum shifting displacement, and left/right shifting displacement, when testing with real wind parameters from KLAF airport. </p>