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Andrea Anguiano

Undergraduate Student

Andrea Anguiano

2019 - 2021

Built a high-performance Lagrangian oil spill model and forecast system for the Gulf of Mexico (UNAM).

Research areas

  • SciML

Biography

Research

Andrea Anguiano worked with Olmo Zavala Romero (2019–2021) on operational oil spill forecasting for the Gulf of Mexico. Andrea's undergraduate thesis, "Sistema de Pronóstico de Derrames de Petróleo en el Golfo de México" (Oil Spill Forecast System for the Gulf of Mexico), supervised by Zavala Romero, had three parts: a high-performance Lagrangian oil spill model written in Julia, an operational forecast system with a public website, and a web-based oil spill simulator. The code is available on GitHub.

Background

Andrea earned a Licenciatura en Ciencias de la Tierra (B.S. in Earth Sciences) from the Facultad de Ciencias, Universidad Nacional Autónoma de México (UNAM), in 2022, working with UNAM's Ocean–Atmosphere Interaction (IOA) group.

Selected publication

A. Anguiano-García, O. Zavala-Romero, J. Zavala-Hidalgo, J. A. Lara-Hernández, R. Romero-Centeno, "High Performance Open Source Lagrangian Oil Spill Model," in Supercomputing, Communications in Computer and Information Science, Springer, 2019. doi:10.1007/978-3-030-10448-1_11

Software and methods

Julia, Lagrangian particle modeling, operational forecasting, and web-based geospatial visualization.

Education

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No education history is listed for this profile yet.

Publications

1 item
Conference 2019 High Performance Open Source Lagrangian Oil Spill Model Andrea Anguiano Olmo Zavala-Romero Jorge Zavala-Hidalgo Julio Antonio Lara-Hernandez

In the lab Andrea Anguiano Olmo Zavala-Romero

. An oil spill particle dispersion model implemented in Julia, a highperformance programming language, and Matlab is described. The model is based on a Lagrangian particle tracking algorithm with a second-order RungeKutta scheme. It uses ocean currents from the Hybrid Coordinate Ocean Model (HYCOM) and winds from the Weather Research and Forecasting Model (WRF). The model can consider multiple oil components according to their density and different types of oil decay: evaporation, burning, gathering, and exponential degradation. Furthermore, it allows simultaneous modeling of oil spills at multiple locations. The computing performance of the model is tested in both languages using an analogous implementation. A case study in the Gulf of Mexico is described.

Blog

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