The study of wind behavior along railway infrastructures is essential to ensure safety and operational continuity. Mitigating wind-related risks represents a significant challenge, especially in regions exposed to strong crosswind events, gust fronts of sudden wind shear, which can compromise train stability and operational reliability. In recent years, reanalysis-based tools have been widely adopted for estimating wind conditions over large areas, especially in support of wind energy applications. However, these approaches have proven inadequate for applications requiring high spatial precision and the assessment of rare, high-impact events, such as wind conditions along railway lines with return periods of 50 years or more. The objective of this thesis is to develop a methodology for estimating wind conditions along railway lines based on measurements from nearby anemometric stations. To this end, a high-resolution computational approach is developed using the open-source CFD software OpenFOAM, enabling accurate simulation of wind fields over complex terrain. A preliminary validation step is carried out through a simplified test case to benchmark CFD results against analytical atmospheric models. The methodology is then applied to two different case studies: the Milano–Novara railway line, located in flat terrain, and the Rome–Naples line, which traverses complex mountainous regions. In each case, transfer coefficients-dimensionless ratios that relate wind conditions at the line to those measured at nearby anemometric stations-obtained via CFD simulations are compared to those derived from the simplified ESDU approach, highlighting both areas of agreement and divergence, and exploring the physical mechanisms driving such differences.
Lo studio del comportamento del vento lungo le infrastrutture ferroviarie è fondamentale per garantire la sicurezza e la continuità operativa. Mitigare i rischi legati al vento rappresenta una sfida significativa, soprattutto nelle aree soggette a intensi venti trasversali, fronti di raffica o improvvisi fenomeni di wind shear, che possono compromettere la stabilità del treno e l’affidabilità del servizio. Negli ultimi anni, strumenti basati su rianalisi sono stati ampiamente adottati per stimare le condizioni di vento su vaste aree, in particolare a supporto delle applicazioni nel settore eolico. Tuttavia, tali approcci si sono dimostrati inadeguati per contesti che richiedono elevata precisione spaziale e la valutazione di eventi rari e ad alto impatto, come le condizioni di vento lungo le linee ferroviarie associate a tempi di ritorno di 50 anni o più. L’obiettivo di questa tesi è sviluppare una metodologia per stimare le condizioni di vento lungo le linee ferroviarie a partire da misurazioni effettuate presso stazioni anemometriche vicine. A tal fine, è stato elaborato un approccio computazionale ad alta risoluzione, basato sul software open-source OpenFOAM, che consente di simulare con precisione il campo di vento su terreni complessi. Una fase preliminare di validazione è stata condotta attraverso un caso test semplificato, con l’obiettivo di confrontare i risultati CFD con modelli atmosferici analitici. La metodologia è stata quindi applicata a due casi studio distinti: la linea ferroviaria Milano–Novara, localizzata in un’area pianeggiante, e la tratta Roma–Napoli, che attraversa territori montuosi complessi. In ciascun caso, i coefficienti di trasferimento—parametri adimensionali che mettono in relazione le condizioni di vento lungo la linea con quelle misurate presso stazioni anemometriche vicine—sono stati determinati mediante simulazioni CFD e confrontati con i valori derivati dall’approccio semplificato ESDU, evidenziando sia aree di accordo che divergenze, e analizzando i meccanismi fisici alla base di tali differenze.
CFD simulation of atmospheric wind for crosswind risk estimation of railway lines in complex terrains
DEURANDI, DAVID
2024/2025
Abstract
The study of wind behavior along railway infrastructures is essential to ensure safety and operational continuity. Mitigating wind-related risks represents a significant challenge, especially in regions exposed to strong crosswind events, gust fronts of sudden wind shear, which can compromise train stability and operational reliability. In recent years, reanalysis-based tools have been widely adopted for estimating wind conditions over large areas, especially in support of wind energy applications. However, these approaches have proven inadequate for applications requiring high spatial precision and the assessment of rare, high-impact events, such as wind conditions along railway lines with return periods of 50 years or more. The objective of this thesis is to develop a methodology for estimating wind conditions along railway lines based on measurements from nearby anemometric stations. To this end, a high-resolution computational approach is developed using the open-source CFD software OpenFOAM, enabling accurate simulation of wind fields over complex terrain. A preliminary validation step is carried out through a simplified test case to benchmark CFD results against analytical atmospheric models. The methodology is then applied to two different case studies: the Milano–Novara railway line, located in flat terrain, and the Rome–Naples line, which traverses complex mountainous regions. In each case, transfer coefficients-dimensionless ratios that relate wind conditions at the line to those measured at nearby anemometric stations-obtained via CFD simulations are compared to those derived from the simplified ESDU approach, highlighting both areas of agreement and divergence, and exploring the physical mechanisms driving such differences.| File | Dimensione | Formato | |
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2025_07_Deurandi_Tesi_01.pdf
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2025_07_Deurandi_Executive_Summary_02.pdf
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https://hdl.handle.net/10589/239822