Porosity Analysis

Porosity analysis focuses on accurately determining the pore space within materials, crucial for understanding material properties and performance in diverse applications like additive manufacturing and reservoir modeling. Current research emphasizes the use of machine learning, particularly deep learning architectures like UNets and Vision Transformers, to analyze various data sources including X-ray computed tomography scans, thermal images, and acoustic emission signals, often incorporating physics-informed models to improve accuracy and robustness. These advancements enable faster, more efficient, and potentially in-line porosity analysis, leading to improved quality control in manufacturing and enhanced reservoir characterization in the geosciences.