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Polymer Formulation Optimization Software - KLOAD
By Dr. Roozbeh Dargazany, Ph.D., Michigan State University | 2nd most-cited author in rubber aging globally
Developing a new polymer or rubber compound typically requires 10–50 formulation iterations and 6–18 months of testing—with each validation cycle costing $100K+ and still relying on inaccurate Arrhenius extrapolation.
K-Load is polymer formulation optimization software that replaces trial-and-error development with AI-driven digital twin simulation, allowing you to test fewer formulations and predict long-term performance before manufacturing.
Know whether your material will survive 10–20 years in harsh environments—before you produce it.
K-SUITE PRODUCTS POWERING K-LOAD
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-SENSE
CABLE INSULATION AGING
cable insulation aging prediction software
• FDR/NDE diagnostic digital twin
• Nuclear cable condition monitoring
• DOE SBIR / PNNL collaboration
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.
Start your 30-day free trial.
No credit card. No commitment. Replace your next aging test with a digital twin.
POLYMER FORMULATION OPTIMIZATION SOFTWARE — HOW IT WORKS
Replace Trial-and-Error with Digital Twins
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Train models using minimal experimental datasets
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Predict long-term behavior across temperatures, loads, and environments
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Eliminate unnecessary formulation iterations
Rubber Compound Aging Prediction
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Capture thermal oxidation, diffusion-limited oxidation (DLO), and hydrolysis
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Predict stress–strain and relaxation behavior over time
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Validate formulations without full aging campaigns
Accelerated Aging Test Replacement
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Replace ISO-based Arrhenius workflows
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Simulate multi-mechanism degradation instead of single-factor extrapolation
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Reduce qualification timelines from months to days
Our Case Study
This case study highlights the use of the K-Load Thermal Aging Module to model the long-term reliability of nitrile butadiene rubber (NBR) under accelerated aging.
Elastomer seals, gaskets, and packers used in oil and gas, geothermal, and petrochemical industries face unique challenges when exposed to hot brine...
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-Load Polymer Software
Constitutive modeling and loss of performance due to coupled aging fatigue
K-Load: Simulating Multi-stressor Damage
Available Modules
What is K-Load?
Case Studies
Download our case studies here
Case Study: Predicting Thermal Aging of NBR with Digital Twin Modeling
This case study highlights the use of the K-Load Thermal Aging Module to model the long-term reliability of nitrile butadiene rubber (NBR) under accelerated aging. Stress–strain and relaxation data from unaged samples and two accelerated exposures at 80 °C (1.5 and 6 days) were used to train the digital twin. These datasets captured early degradation trends, enabling the model to simulate both intermittent constitutive behavior and long-term relaxation response of elastomers.
To validate performance, the trained model was applied to predict NBR behavior at 60 °C. Notably, no 60 °C data were used in training, making this a pure forward prediction. The predictions closely matched experimental data, demonstrating the accuracy of the hybrid physics-informed machine learning approach. Unlike conventional Arrhenius models, K-Load accounts for multi-mechanism kinetics, reducing the number of required test conditions. This enables faster, more reliable qualification of rubber seals, gaskets, and elastomeric components in aerospace, automotive, and energy applications.
Case Study 2 : Predicting Relaxation and Shelf-Life of Elastomers in Oil & Gas Environments
Elastomer seals, gaskets, and packers used in oil and gas, geothermal, and petrochemical industries face unique challenges when exposed to hot brine, hydrocarbons, and high-pressure high-temperature (HPHT) fluids. One critical failure mode is stress relaxation, where constant strain leads to gradual stress loss due to thermal oxidation, hydrolysis, and network degradation. This directly impacts shelf-life, sealing reliability, and long-term safety of downhole and surface equipment.
Using K-Load’s Relaxation and Diffusion-Limited Oxidation (DLO) modules, a digital twin was trained with a minimal dataset (relaxation at 20% strain in air at 60 °C, 50% in air at 100 °C, and 25% in oil at 60 °C). With this input, the model accurately predicted relaxation behavior across multiple temperatures (60–100 °C), pre-stretch levels (20–50%), and environments (air vs. oil). The oil retraining process captured hydrolysis and ingress effects while assuming non-corrosive oil, extending predictions to field-relevant conditions.
This capability has broad relevance across oil and gas, automotive, aerospace, nuclear, and pharmaceutical industries, where polymers must maintain functionality under thermal, chemical, and mechanical stress. By reducing experimental campaigns by up to 70%, K-Load enables faster qualification of elastomers, improved lifetime prediction, and optimized maintenance planning, ultimately lowering operational risk.
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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
Brochures
K-Load is a physics-informed simulation tool that enables engineers and scientists to:
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Predict polymer response to static and dynamic loading
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Analyze cyclic fatigue, creep, and stress-relaxation behavior
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Model multiaxial loading and time-dependent mechanical degradation
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Account for temperature-coupled mechanical aging and viscoelastic loss
Built using multi-physics solvers and validated with lab data, K-Load supports digital qualification and helps reduce reliance on long-term bench testing.