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Digital twin for hydrogen refueling stations: An analytical study for safe and efficient operations
(2023)
This analytical overview is the initial study in developing the digital sensors twin for the hydrogen refueling station. The research includes a comprehensive analysis of the current literature, refueling protocol, standards, mathematical model, simulation model, and trends in digital twins and H2 technologies. Furthermore, this study has explored the various HRS attributes, such as leakage, temperature, pressure, and hydrogen flow, and identified different use cases of the hydrogen fuel station to build a digital sensor twin. Various real gas equations, such as the Van der Waals and Able-Noble equation of state (EOS), are applied to analyze the key factors and parameters affecting hydrogen and the MATLAB simulation model to validate the key elements and parameters. This study also focuses on identifying and addressing research gaps in hydrogen technology, contributing to advancing hydrogen infrastructure, and supporting the global transition to cleaner energy solutions.
Visualization of automated multi‐sensor NDT assessment of concrete structures (NDT Data Fusion)
(2017)
Nondestructive testing(NDT) of concrete buildings allows efficient repair measures. Multi-sensor platforms collect large data sets but the data analysis is typically performed manually. Data Fusion uses the full potential of a multi-sensory data set in order to:
- improve information quality (reliability, robustness, accuracy, clarity, completeness)
- enable automated algorithm based data analysis.
This poster summarizes results of the IGSTC-project entitled "NDT-Data Fusion" (short title) and demonstrates a significant improvement in the testing performance for the example of corrosion detection.