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Cable Insulation Aging Prediction Software - KSENSE
By Dr. Roozbeh Dargazany, Ph.D., Michigan State University | 2nd most-cited author in rubber aging globally
Cable failures in nuclear and industrial systems are rarely sudden—they are the result of years of thermal, radiation, and chemical degradation in insulation materials. Yet most operators still rely on periodic inspection or conservative replacement schedules.
K-Sense is cable insulation aging prediction software that uses your existing FDR and NDE data to predict remaining useful life (RUL) in real time—without waiting for failures or multi-year testing.
Turn your existing diagnostic data into actionable lifetime predictions.
K-SUITE PRODUCTS POWERING K-SENSE
K-LOAD
FORMULATION OPTIMIZATION
polymer formulation optimization software
• Test 10× fewer compounds
• Compress 18-month cycles to days
• Accelerated aging test replacement
FREE 30-DAY TRIAL ➤
K-FAIL
DAMAGE ACCUMULATION
polymer damage accumulation simulation
• Thermal + mechanical + radiation + moisture
• Aerospace & naval elastomer durability
• DOD Space Force validated
FREE 30-DAY TRIAL ➤
K-EXTREME
EXTREME ENVIRONMENTS
polymer simulation extreme environments
• HPHT downhole & geothermal wells
• Radiation & space-grade conditions
• 217 impressions, zero clicks fixed
FREE 30-DAY TRIAL ➤
Accelerating the Digital Transformation of Industry with Simulation
Every industy faces unique, constantly evolving challenges. K- Suite delivers the expertise, capabilities and tools to transform the design and production processes of industries.
Aerospace
Predict elastomer durability under extreme thermal + mechanical stress. DOD Space Force validated.
Space Electronics
Polymer aging under radiation and vacuum. K-Extreme covers space-grade and PEM applications.
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Nuclear
Cable insulation remaining life prediction. FDR/NDE digital twin via K-Sense. DOE SBIR funded.
EV & Energy
Battery seal and insulation durability. Multi-stressor simulation: heat, vibration, moisture.
Oil & Gas
HPHT downhole seal performance. CNPC-validated. 35-day prediction vs. 6-month test.
Polymer Aging & Durability Simulation Software, Validated by Real-World Data
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CNPC oil-well sealant trials
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Lab measurements validated
K-Suite vs. traditional test
vs. Arrhenius-only methods
“In CNPC oil-well trials, K-Suite predicted 5-year sealant degradation with 95% accuracy — replacing a 6-month/$180K physical test.”
Scientific basis: Dargazany et al., “A network evolution model for the anisotropic Mullins effect in carbon black filled rubbers,” International Journal of Solids and Structures, 2012.
Industrial Case Study : Aged Epoxy
In our latest benchmark on engineering-grade polymers, K-SENSE demonstrated breakthrough results using only sparse induction-period data.
Elastomers, Thermoplastics and composites
Don’t guess material health. Quantify it through images.
Works with Your Existing Engineering Stack
ANSYS Marketplace
Coming Q3 2026
MSC Software
Compatible
Abaqus / FEA
Compatible
Python / REST API
Developer access
Start your 30-day free trial.
No credit card. No commitment. Replace your next aging test with a digital twin.
CABLE INSULATION AGING PREDICTION SOFTWARE — HOW IT WORKS
Use Existing FDR Cable Diagnostic Digital Twin
K-Sense integrates directly with:
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Frequency Domain Reflectometry (FDR)
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NDE inspection data
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Imaging and sensor-based diagnostics
Instead of raw signal interpretation, K-Sense converts this data into:
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Remaining Useful Life (RUL)
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Degradation rate
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Failure probability
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Nuclear Cable Condition Monitoring (Continuous Insight)
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Track insulation degradation under:
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Radiation exposure
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Thermal aging
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Oxidation and crosslinking
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Replace periodic inspection with continuous predictive monitoring
NDE Polymer Remaining Life Prediction
K-Sense uses physics-informed AI to connect observable signals (color, dielectric response, imaging) to:
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Mechanical properties (elongation, tensile strength)
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Chemical degradation kinetics
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Long-term performance
Let’s Get Started
If you're facing engineering challenges, our team is here to assist. With a wealth of experience and a commitment to innovation, we invite you to reach out to us. Let's collaborate to turn your engineering obstacles into opportunities for growth and success. Contact us today to start the conversation.
K-Sense
K-Sense: Real-Time Health Monitoring through Imaging
via Physics-Informed Colorimetry
K-Sense: Optical Diagnostics for Polymer Aging
Outputs:
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Failure Properties
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Color Change
03
Remaining Useful Life
Imaging for Condition Monitoring
The Problem: Traditional reliability models require multi-year physical tests to certify a single compound which can be elastomers, epoxies, thermoplastics, and thermosets.
K-Sense Physics-based AI architectures understand the underlying chemistry of oxidation and cross-linking.
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60% Reduction in Testing Duration
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Physics-Driven Extrapolation
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High Confidence Ratio by Tracing Compound Specific Kinetics
K-Sense Superiority to Statistical Models
We validate our digital twins using a rigorous two-step protocol that ensures your field data matches our lab-trained models.
Step 1: Limited Training Set required
We ingest data from coupon-level accelerated tests (Thermal, Radiation, or Synergistic). This "seeds" the PINN with the material’s specific degradation kinetics.
Step 2: High Accuracy in Long-Term Predictions
We compare K-Sense predictions against independent "Long-Tests"—real-time service data or extended duration lab tests. The Result: Our models consistently show high agreement with long-term mechanical decay (Elongation at Break, Tensile Strength, and Modulus) that legacy Arrhenius models simply cannot capture.
Industrial Case Study : Aged Epoxy
Predicting 3 Months of Performance from 15 Days of Lab Testing
In our latest benchmark on engineering-grade polymers, K-SENSE demonstrated breakthrough results using only sparse induction-period data.
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Polymer degradation
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Polymer aging prediction
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Polymer durability
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Polymer life prediction
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Polymer performance degradation
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Polymer material aging
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Polymer part life cycle
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Polymer component degradation
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Polymer part aging
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Polymer part life prediction