The transportation sector plays a crucial role in the global economy, with freight trains being a key component in the efficient movement of goods over long distances. However, the energy consumption and aerodynamic performance of freight trains have become critical concerns. Improving the aerodynamic efficiency of freight trains can significantly reduce fuel consumption, offering both economic and environmental benefits. In recent years, Computational Fluid Dynamics (CFD) has emerged as a powerful tool to study and optimize the aerodynamic properties of various vehicles, including freight trains. Standard regulations and guidelines towards modelling a CFD model for freight trains to study the effects of drag is expected soon. The motivation of this thesis will focus on providing guidelines to create a CFD model for a freight train to analyse the effect of drag. In CEN norms, the threshold for relative error between the results of CFD model and experimental test is less than 15%. To achieve this, numerical simulations were performed using OpenFOAM software with RANS model and k−ω SST turbulence model. Primarily, Domain analysis was done to neglect the boundary effects. Next, a mesh sensitivity was accomplished to determine the optimal grid intensity to obtain accurate results. Then, the Reynold’s effect Independence was carried out to verify the reliability of scaled models to predict the flow as in a real system. This CFD model with a specific loading gap configuration was simulated and then validated with the experimental data from wind tunnel test. Later, this validated CFD model was used to study the effect on the coefficient of drag of various loading gap configurations in upstream and downstream of the test container. This analysis explained that, after a critical gap length was attained, the flow acts as a free flow towards the test container and the value of the drag coefficient tends asymptotically towards the maximum value. After which, features were added on the geometry of test container of the freight train to realise it as a realistic container and simulated to study its effect on drag. With features being added the drag coefficient increased and its relative error with the experimental results were lower than those of the original geometry. At last, this CFD model was further developed to simulate the Crosswind conditions to qualitatively analyse its effect on freight trains.
Il settore dei trasporti svolge un ruolo cruciale nell'economia globale, con i treni merci che sono una componente chiave per il movimento efficiente delle merci su lunghe distanze. Tuttavia, il consumo energetico e le prestazioni aerodinamiche dei treni merci sono diventati un problema critico. Il miglioramento dell'efficienza aerodinamica dei treni merci può ridurre significativamente il consumo di carburante, offrendo vantaggi sia economici che ambientali. Negli ultimi anni, la fluidodinamica computazionale (CFD) è emersa come un potente strumento per studiare e ottimizzare le proprietà aerodinamiche di vari veicoli, compresi i treni merci. Sono attese a breve norme e linee guida standard per la modellazione di un modello CFD per i treni merci per studiare gli effetti della resistenza aerodinamica. La motivazione di questa tesi si concentrerà sulla fornitura di linee guida per la creazione di un modello CFD per un treno merci per analizzare l'effetto della resistenza aerodinamica. Secondo le norme CEN, la soglia di errore relativo tra i risultati del modello CFD e le prove sperimentali è inferiore al 15%. Per raggiungere questo obiettivo, sono state eseguite simulazioni numeriche utilizzando il software OpenFOAM con modello RANS e modello di turbolenza k-ω SST. In primo luogo, l'analisi del dominio è stata eseguita per trascurare gli effetti di contorno. Successivamente, è stata eseguita una sensibilità della maglia per determinare l'intensità ottimale della griglia per ottenere risultati accurati. È stata poi effettuata l'Indipendenza dell'effetto Reynold per verificare l'affidabilità dei modelli in scala nel prevedere il flusso come in un sistema reale. Questo modello CFD con una specifica configurazione del gap di carico è stato simulato e poi convalidato con i dati sperimentali della prova in galleria del vento. Successivamente, il modello CFD convalidato è stato utilizzato per studiare l'effetto sul coefficiente di resistenza aerodinamica di varie configurazioni di fessure di carico a monte e a valle del contenitore di prova. L'analisi ha rivelato che, una volta raggiunta una lunghezza critica della fessura, il flusso si comporta come un flusso libero verso il container di prova e il valore del coefficiente di resistenza aerodinamica tende asintoticamente al valore massimo. Successivamente, sono state aggiunte caratteristiche alla geometria del container di prova del treno merci per renderlo realistico e sono state effettuate simulazioni per studiarne l'effetto sulla resistenza aerodinamica. Con l'aggiunta delle caratteristiche, il coefficiente di resistenza aerodinamica è aumentato e l'errore relativo con i risultati sperimentali è stato inferiore a quello della geometria originale. Infine, questo modello CFD è stato ulteriormente sviluppato per simulare le condizioni di vento laterale e analizzare qualitativamente il suo effetto sui treni merci.
CFD modelling guidelines to analyse the effects of drag on freight trains
Thirusala Suresh, Venkatachalapathy
2023/2024
Abstract
The transportation sector plays a crucial role in the global economy, with freight trains being a key component in the efficient movement of goods over long distances. However, the energy consumption and aerodynamic performance of freight trains have become critical concerns. Improving the aerodynamic efficiency of freight trains can significantly reduce fuel consumption, offering both economic and environmental benefits. In recent years, Computational Fluid Dynamics (CFD) has emerged as a powerful tool to study and optimize the aerodynamic properties of various vehicles, including freight trains. Standard regulations and guidelines towards modelling a CFD model for freight trains to study the effects of drag is expected soon. The motivation of this thesis will focus on providing guidelines to create a CFD model for a freight train to analyse the effect of drag. In CEN norms, the threshold for relative error between the results of CFD model and experimental test is less than 15%. To achieve this, numerical simulations were performed using OpenFOAM software with RANS model and k−ω SST turbulence model. Primarily, Domain analysis was done to neglect the boundary effects. Next, a mesh sensitivity was accomplished to determine the optimal grid intensity to obtain accurate results. Then, the Reynold’s effect Independence was carried out to verify the reliability of scaled models to predict the flow as in a real system. This CFD model with a specific loading gap configuration was simulated and then validated with the experimental data from wind tunnel test. Later, this validated CFD model was used to study the effect on the coefficient of drag of various loading gap configurations in upstream and downstream of the test container. This analysis explained that, after a critical gap length was attained, the flow acts as a free flow towards the test container and the value of the drag coefficient tends asymptotically towards the maximum value. After which, features were added on the geometry of test container of the freight train to realise it as a realistic container and simulated to study its effect on drag. With features being added the drag coefficient increased and its relative error with the experimental results were lower than those of the original geometry. At last, this CFD model was further developed to simulate the Crosswind conditions to qualitatively analyse its effect on freight trains.File | Dimensione | Formato | |
---|---|---|---|
2024_12_THIRUSALA SURESH_Thesis_01.pdf
solo utenti autorizzati a partire dal 20/11/2025
Dimensione
5.33 MB
Formato
Adobe PDF
|
5.33 MB | Adobe PDF | Visualizza/Apri |
2024_12_THIRUSALA_SURESH_Executive Summary_02.pdf
solo utenti autorizzati a partire dal 20/11/2025
Dimensione
932.35 kB
Formato
Adobe PDF
|
932.35 kB | Adobe PDF | Visualizza/Apri |
I documenti in POLITesi sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
https://hdl.handle.net/10589/230491