Blog

Bridging the Gap between Local Adhesion Capacity and Macroscopic Fracture Energies: A Study of Niobium/Alumina Bicrystal Specimens

/

In the field of materials science, it is important to understand the relationship between the microscopic properties of a material and its macroscopic behavior. In the presented work, the authors aimed to clear up the theoretical interlink between local adhesion capacity and macroscopic fracture energies by bridging different length scales, such as nano-, meso-, and […]

Bridging the Gap between Local Adhesion Capacity and Macroscopic Fracture Energies: A Study of Niobium/Alumina Bicrystal Specimens Read More »

The Future is blowing in the wind: Machine Learning takes on the Damage Detection in Composite Materials used in Wind Turbine Blades

/

Wind turbines are a crucial source of renewable energy, but their blades are constantly exposed to harsh weather conditions, which can cause damage over time. To ensure the safety and efficiency of wind turbines, it is essential to detect damage in the composite materials used to make the blades. However, detecting damage in composites can

The Future is blowing in the wind: Machine Learning takes on the Damage Detection in Composite Materials used in Wind Turbine Blades Read More »

Uncharted Waters: A Deep Dive into Assessing the Fatigue Life of Subsea Pipelines

/

Subsea cables and pipelines are the backbone of the offshore infrastructure, playing a critical role in transporting energy and fuel. These pipelines and cables are essential for keeping the lights on and powering our homes and businesses, but with this importance comes a great responsibility to ensure their safe and reliable operation. One of the

Uncharted Waters: A Deep Dive into Assessing the Fatigue Life of Subsea Pipelines Read More »

Revolutionizing Wind Farm Efficiency: New Machine Learning Technique Predicts Optimal Layouts in Seconds

/

Researchers have developed a novel machine learning and pattern recognition approach to solving the wind farm layout optimization problem (WFLOP). The traditional row-by-row grids of turbines seen in many wind farms today can suffer from a 10-15% annual energy production loss due to inter-turbine turbulence called the wake effect. To minimize this loss, an optimal

Revolutionizing Wind Farm Efficiency: New Machine Learning Technique Predicts Optimal Layouts in Seconds Read More »

Difference between Hashin Damage Model and Johnshon Cook Damage Model

/

This short blog post is based on the one of the question I have received from a researcher/student who follows my channel and webpage. When simulating the behaviour of materials under high strain rates or extreme loading conditions, it’s important to accurately predict when and how they will fail. Two commonly used models for this

Difference between Hashin Damage Model and Johnshon Cook Damage Model Read More »

Ductile Damage Simulation in ABAQUS CAE – Through Explicit and Standard

/

In this blog I take you through ductile damage modelling in ABAQUS CAE using both explicit and standard analysis steps. After going through this video you will be able to answer and perform the following with full confidence. How to simulate ductile failure of a metal in ABAQUS? Tips on improving convergence in simulating ductile

Ductile Damage Simulation in ABAQUS CAE – Through Explicit and Standard Read More »

Shopping Cart
Scroll to Top