K-Extreme | Polymer Simulation in Extreme Environments

K-Nde: Polymer Simulation Extreme Environments

Your cables have been in service for 40 years. You can't test them without a full shutdown. K-NDE reads your FDR and TDR signals and tells you exactly where the damage is.

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ElastoSure Products Powering K-NDE

K-LOAD

FORMULATION OPTIMIZATION

polymer formulation optimization software

• Test 10× fewer compounds

• Compress 18-month cycles to days

• Accelerated aging test replacement

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FREE 30-DAY TRIAL ➤

Real-World Proof Behind the Polymer Aging & Durability Simulation Software

Prediction Accuracy

95%

For long-term durability prediction

Experimental Tests

80,000+

Used for training and validation

vs. 6 Months

35 Days

Replacing long-weathering tests

Faster Analysis

5–10×

Compared to traditional FE models

Accelerating the Digital Transformation of Industry with Simulation

Every industy faces unique, constantly evolving challenges. ElastoSure delivers the expertise, capabilities and tools to transform the design and production processes of industries.

Oil & Gas

Model seal and elastomer degradation under heat, pressure, H2S, chemicals, and long-duration downhole exposure.

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Defense & Aerospace

Support mission-life prediction for polymer components under extreme environments, storage, radiation, thermal cycling, and mechanical fatigue.

Rubber & Elastomers

Predict when seals, O-rings, gaskets, and elastomer components approach leakage, stiffness loss, cracking, or compression-set thresholds.

K-NDE

Machine-learned survivability estimation.

Summary: K-Extreme is a machine-learned engine that provides conservative estimates of survivability by calculating the minimum damage capacity needed to survive single-event effects (SEE) such as: loss-of-coolant accidents in nuclear reactors, solar flares for space applications and nuclear detonation simulations for strategic defense applications. K-Extreme then takes into account the available data on different SEE and uses them to predict survivability in case of a new SEE.