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sensor measurements to embankment responses will be derived and validated using field data. These relationships will provide a framework for translating routinely collected monitoring data into actionable
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study. The research will begin with the analysis of baseline and historical data collected from wayside sensors installed on selected instrumented railway bridges. Building on these insights, an on-board
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-induced dynamic behaviour. Transfer functions linking LDV, ABA, TG, and wayside sensor measurements to embankment responses will be derived and validated using field data. These relationships will provide a
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of railway tracks on bridges, using Dutch railway infrastructure as a primary case study. The research will begin with the analysis of baseline and historical data collected from wayside sensors installed
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energy, climate, digitalisation, artificial intelligence (AI), and smart mobility every day. Our education and research are directly aligned with what society needs now and in the future. At TU Delft, our
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, artificial intelligence (AI), and smart mobility every day. Our education and research are directly aligned with what society needs now and in the future. At TU Delft, our people make the difference. With
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advanced experiments for investigating cryogenics two-phase flow. A second objective is to build cryogenic sensors for heat and flow measurements, in collaboration with the Von Karman Institute (VKI, Belgium
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intelligence (AI), and smart mobility every day. Our education and research are directly aligned with what society needs now and in the future. At TU Delft, our people make the difference. With their knowledge
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combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society