Search
Now showing items 1-6 of 6
Use of Seismic Analyses for the Wind Energy Industry
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: This paper proposes new seismic-based methods for use in the wind energy industry with a focus on wind turbine condition monitoring. Fourteen Streckeisen STS-2 Broadband seismometers and two three-dimensional (3D) sonic ...
Effects of Onshore and Offshore Environmental Parameters on the Leading Edge Erosion of Wind Turbine Blades: A Comparative Study
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: The presence of rain-induced leading edge erosion of wind turbine blades (WTBs) necessitates the development of erosion models. One of the essential parameters for erosion modeling is the relative impact velocity between ...
Surrogate-Based Time-Dependent Reliability Analysis for a Digital Twin
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: A mature digital twin (DT) is supposed to enable engineers to accurately evaluate the real-time reliability of a complex engineering system. However, in practical engineering problems, reliability analysis (RA) often ...
A New Sequential Sampling Method for Surrogate Modeling Based on a Hybrid Metric
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Sequential sampling methods have gained significant attention due to their ability to iteratively construct surrogate models by sequentially inserting new samples based on existing ones. However, efficiently and accurately ...
A New Validation Metric for Models With Correlated Responses Using Limited Experimental and Simulation Data
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Model validation is the process of determining the degree to which a model is an accurate representation of the real object. Most of the existing model verification metrics rely on massive data, which are expensive to ...
Toward a Digital Twin: Time Series Prediction Based on a Hybrid Ensemble Empirical Mode Decomposition and BO-LSTM Neural Networks
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Precise time series prediction serves as an important role in constructing a digital twin (DT). The various internal and external interferences result in highly nonlinear and stochastic time series. Although artificial ...