Quickly & accurately calculate material fatigue performance with our Fatigue Tool

As a CAE and mechanical engineer, who selects materials for various applications, it is important for you to estimate the lifetime of the product under repetitive cycle loads. Comparing a material’s long-term fatigue performance at different temperatures and relative humidity is necessary to ensure you pick the appropriate material. 

Use the Fatigue Tool for all your calculations, simulations and reliability analysis 

We built the Fatigue Tool so you can be efficient and effective picking the proper material solution. It provides accurate and consistent fatigue data for a variety of grades and conditions, which is an essential part of the design and reliability workflow, and product development cycle.

The Fatigue Tool is most important to utilize during the initial product design phase. It can also be used when the fatigue performance of an existing product is not sufficient and another material with better fatigue resistance needs to be chosen. The Fatigue Tool gives you the needed data to select the best material for the specific application you are designing and to evaluate its long-term performance. 

You can obtain material data immediately

You no longer must wait weeks to get material data—when you use our Fatigue Tool for calculations, simulations and reliability analysis, you get data immediately. Since SN curves are an essential part of product design and development, the faster you obtain the relevant data the better to keep your project on track. You can compare the data on the website or download it in an Excel format. 

The technology behind the Fatigue Tool 

To build the Fatigue Tool, we combined experimental data for various grades and conditions that was historically measured to provide dataset for the tool. However, there are many cases where requirements are quite broad. For example, for new applications, a design or reliability engineer will want data at different temperatures for different materials. To provide standard fatigue data at any conditions we developed a fatigue model.

Using underlying physics, the fatigue model is based on a big experimental dataset and further uses machine learning techniques for parametrization, optimization and statistical and accuracy information. This hybrid modeling approach is used to predict fatigue lifetime and is validated on all data that was measured over the years to ensure consistency and accuracy.

The Fatigue Tool is based on an isothermal high-cycle tension fatigue model that generates a standard SN curve (R = 0.1, ISO 527-1A geometry) for any material at required environmental conditions, such as temperature and relative humidity.