Understanding how high-performance computation (HPC) supports real-time structural health monitoring (SHM) by enhancing data acquisition, signal processing, damage detection, and decision-making.
Explore how GPUs achieve exceptional computational power through their hierarchical architecture and embarrassingly parallel workflows, with a focus on leveraging PyTorch for efficient processing on both Nvidia GPUs and Apple Silicon.
On December 5, 2013, a mysterious series of booms startled Tamsui residents in Taiwan. Using seismic and infrasound data, we uncovered the event’s origin—a meteor shockwave. This rare phenomenon allowed us to reconstruct the meteor’s trajectory and estimate its energy, highlighting the value of geophysical monitoring in studying atmospheric events.
Learn how RabbitMQ enables seamless and reliable communication between distributed systems. This article explores setting up RabbitMQ using Docker, simulating seismic waveform data, and creating efficient producers and consumers with both blocking and asynchronous connections. Gain practical insights into building scalable messaging systems for real-time data processing and beyond.
Earthquakes shake buildings in all three directions, but why is vertical motion often ignored in design? Thanks to gravity, high vertical stiffness, and built-in safety margins, structures are naturally robust in the vertical direction. However, certain components and seismic codes still require careful consideration. Learn when vertical effects matter and why horizontal motion is more critical.
Databricks is a cloud-based platform that simplifies big data analytics by integrating powerful cluster management with an intuitive notebook interface. Perfect for beginners, its free community edition offers a 15GB cluster for experimentation. With built-in support for Python, SQL, and Apache Spark, Databricks enables users to upload, process, and analyze data effortlessly.
Discover how Genetic Algorithms can be applied to solve the earthquake location problem in seismology. This post walks through generating synthetic seismic data, implementing a GA to estimate earthquake locations, and visualizing results. While effective, the approach has limitations, including simplified assumptions and constraints.
The PyGMT library in Python simplifies the creation of high-resolution topographic maps by providing built-in shorelines, country borders, and topographic data. By integrating geopandas, PyGMT enables users to overlay custom shapefile data, making it easy to highlight specific regions on a map. In this post, we demonstrate how to use county boundary data from Taiwan’s government portal to overlay on a high-resolution map of Taiwan, focusing on selected counties. This method provides a flexible, powerful approach for creating visually striking maps with customized geospatial information, applicable to various regions and datasets.
Explore how cloud computing is revolutionizing geophysical and seismological research. From scalable data processing to real-time earthquake monitoring, discover how this technology is unlocking new possibilities for scientists around the world
Docker is revolutionizing how we deploy and manage software applications, offering a simple and efficient way to ensure consistency across different environments. In this beginner-friendly guide, we break down the fundamentals of Docker, explore its key concepts, and walk you through creating your own Docker image using a simple Linux base. Whether you're just getting started with computational tools or looking to streamline your research workflows, this guide will equip you with the knowledge to harness the power of Docker in your geophysics studies.
