Turbines

DigitalClone®

Materials-Based Computational Testing

Overview

DigitalClone is a material science-based technology that predicts the earliest point in time when cracks initiate in the microstructure of rotating mechanical components.

DigitalClone® Live
for Operators

Operators use DigitalClone Live to understand when failures can be expected in their fleet, which assets, systems and critical components will begin to fail.

DigitalClone® Live
for Suppliers

Computational testing is used to predict early failure mechanisms in rotating equipment and for design optimization.

Overview

DigitalClone is a material science-based technology that predicts the earliest point in time when cracks initiate in the microstructure of rotating mechanical components. DigitalClone has a suite of offerings to fit the customer and business needs of both operators and suppliers in the wind energy, transportation and aerospace industries.
Step 1

Step 1.
System Effect, 5 Failure Components

Step 2

Step 2.
Build Material Microstructure Models

Step 3

Step 3.
Build Surface Traction Models

Step 4

Step 4.
Material Microstructure Response

Step 5

Step 5.
Calculate Time to Mechanical Failure

Step 6

Step 6.
Predict Fatigue Life Distribution

DigitalClone® Live
for Operators

Operators use DigitalClone Live to understand when failures can be expected in their fleet, which assets, systems and critical components will begin to fail and which life extension actions will provide the greatest return on investment.

This level of granularity can only be predicted with a material science-based, small data approach. Operators are given multiyear budgets, component replacement forecasts and predictive maintenance schedules that save on O&M spend, prevent unplanned and prolonged downtime and improve the reliability of fielded assets.

DigitalClone® Live
for Suppliers

Computational testing is used to predict early failure mechanisms in rotating equipment and for design optimization.

DigitalClone Computational Test Lab is used by Original Equipment Manufacturers and Suppliers to design new product offerings, simulate trade-off and sensitivity studies and to better understand their designs before they are prototyped and produced. This compliments physical testing and facilitates a reduction in design time and cost.

The software is used to improve reliability and to conduct parametric studies that would be infeasible to do through experimental means. Users are able to test 99% more data points at a 37% reduction in cost.