This paper applies Bayesian inversion to bottom-loss data derived from wind-driven ambient noise measurements from a vertical line array to quantify the information content constraining seabed geoacoustic parameters. The inversion utilizes a previously proposed ray-based representation of the ambient noise field as a forward model for fast computations of bottom loss data for a layered seabed. ...

Nonlinear model structure selection (MSS) is an important step in the modeling theory of the nonlinear system. The proper model structure and model parameters estimation can be used to reduce unnecessary computations and improve the model forecast accuracy. This paper mainly investigates the short-term wind speed forecasting (STWSF) by utilizing the comprehensive MSS technique based on real dat...

accurate estimation of reference evapotranspiration plays a key role in water resources management and irrigation scheduling. the fao penman-monteith (f-p-m) is a reference method for calculation of evapotranspiration that needs temperature, humidity, wind speed and solar radiation. in many stations, it is not an easy task to measure the whole weather variables. thus, in this situation, one mus...

Strong cross-winds may overturn trains, so an understanding of the fluid mechanics is important. To facilitate the proper estimation of the probability of a train overturning, accurate data for the aerodynamic rolling moment about the lee rail is essential. (Of course, many other parameters are required.) The flow of a turbulent cross-wind over a train moving across an embankment is complex, an...

The intermittent nature of the wind creates significant uncertainty in the operation of power systems with increased wind power penetration. Considerable efforts have been made for the accurate prediction of the wind power using either statistical or physical models. In this paper, a method based on Artificial Neural Network (ANN) is proposed in order to improve the predictions of an existing n...

Estimating the power output is one of the elements that determine the techno-economic feasibility of a renewable project. At present, there is a need to develop reliable methods that achieve this goal, thereby contributing to wind power penetration. In this study, we propose a method for wind power error estimation based on the wind speed measurement error, probability density function, and win...

The mesoscale numerical weather prediction model MM5, the 5 generation Pennsylvania State University/NCAR Mesoscale Model, uses a global land-use map to set the physical parameters on the surface characteristics to model the soil-atmosphere processes. These parameters are albedo, emissivity, thermal inertia, roughness length and soil moisture. A new estimation of soil parameters is done for the...

This paper presents a quantitative review of early detection and estimation of fault for wind turbine system. The model-based technique is proposed to provide an assessment of all possible faults for renewable energy sources. The augmented observer is applied to estimate the real physical data of the system sensor faults and states simultaneously. The fault detection and diagnosis is designed t...

In this article we present an approach that enables joint wind speed and wind power forecasts for a wind park. We combine a multivariate seasonal time varying threshold autoregressive moving average (TVARMA) model with a power threshold generalized autoregressive conditional heteroscedastic (power-TGARCH) model. The modeling framework incorporates diurnal and annual periodicity modeling by peri...

Improved aerodynamic mathematical models, for use in aircraft simulation or flight control design, are required when representing nonlinear unsteady aerodynamics. A key limitation of conventional aerodynamic models is the inability to map frequency and amplitude dependent data into the equations of motion directly. In an effort to obtain a more general formulation of the aerodynamic model, rese...