Aerospace

Reduce: Risk, Cost & Uncertainty

DigitalClone® software uses materials-based computational testing to simulate trade-off and sensitivity studies, test new materials, and optimize designs.

Reduce Risk

  • Life product before high-cost physical test phase
  • Ensure new designs meet pre-qualification standards
  • Identify and optimize design performance

Reduce Cost

  • Lower inventory carrying cost
  • Enhance HUMS with DigitalClone life prediction
  • Improve maintenance predictability

Reduce Uncertainty

  • Test different design thresholds
  • 3rd party validation of new product impacts
  • Digitally evaluate new design concepts

Simulate More Test Points, Materials & Parameters Beyond the Limitations of Physical Testing

Complementing your
Physical Testing

8 DATA POINTS

37%

reduction in cost

99%

more data points

3,200 DATA POINTS

SBIR Awards

Agency:
National Science Foundation
Phase:
Phase II

SBIR Phase II: Analytical Modeling and Performance Prediction of Remanufactured Gearbox Components

The Innovation of this Phase II project is developing physics-based analytical models to analyze gearbox components for safety, longevity, reliability and cost by predicting (1) New component performance, and optimal time-to-remanufacture, (2) Qualification of used components for remanufacturing process, and (3) Predicting the remanufactured component performance. Current industry approach is to design, manufacture, operate, and retire assets based on traditional methods, which typically rely on standards-based estimates, historical data/domain experience, physical examination, testing, monitoring, and inspection. This process is extremely time and resource intensive. Further, this process often does not consider the opportunity to use remanufacturing processes to extend/enhance product performance. Sentient technology will address these issues and fulfill the industry requirements. Phase II will expand the Phase I technology to include additional gearbox materials, damage modes and remanufacturing processes in a more comprehensive design and analysis framework capable of predicting optimal time-to-remanufacture and optimizing refurbishing operations to extend the useful life of components. This SBIR technology reduces physical testing using virtual testing, and will assist in remanufacturing of high value, high demand rotorcraft, automotive and wind turbine gearbox components. Hence, it decreases the energy, material resources, and costs associated with manufacturing, and ensures that the product performance is maintained/improved. The broader/commercial impact of the SBIR technology is within aerospace, energy, and transportation industries on high dollar assets that rely on the reliable function of highly engineered (and thus expensive) gearboxes. Our new Advanced Manufacturing partnership based application provides the US manufacturing supply chain a first mover and a sustainable competitive advantage greater than the 6% offshore labor rate advantage. This advantage comes through reuse of high value-added assets optimized for maximum lifetime use, coupled with decreased time and costs associated with traditional physical testing and analysis methods. This is possible based on the high-level of detail included in physics-based models, which (conceptually) decode material information at the microstructure level just as the Human Genome Project decodes genetic information at the DNA level. Our innovation enables the customer to rapidly, cost effectively, and accurately predict a product's lifecycle (design, manufacture, operation, degradation, maintenance, repair/remanufacture, and retirement) at the material, component, and assembly/system scales. We foresee a future opportunity due to the fact that our innovation developed under this NSF grant will give us a competitive advantage of lower costs to provide the software and service. Our cost to deploy the technology is 10X lower than traditional companies in this space....Award Details

Agency:
Department of Defense
Phase:
Phase I

Modeling to Quantify Improved Durability of Superfinish Gear Processing Summary

Under this STTR, Sentient Corporation, along with the Ohio State University GearLab as a research partner, will develop a probabilistic physics-based damage modeling tool for the simulation of superfinished gear components. This model will consider critical surface, material, and load parameters for components manufactured from common gear steels. The model will also analyze superfinished as well as traditionally processed gear surfaces. The results will include virtual test data to be validated against actual test results... Award Details


Agency:
Department of Defense
Phase:
Phase I

Fatigue Crack Initiation Prediction Tool for Rotorcraft Spiral Bevel Gears

Current gearbox life estimation techniques commonly underplay the significance of gear tooth surface fatigue due to the complexity of the phenomenon involved. The Phase I program successfully demonstrated the feasibility of utilizing advanced modeling techniques to predict the onset and propagation of surface and bending fatigue in spiral bevel gears, including an analysis of mixed-elastohydrodynamic lubrication and damage accumulation in the material. Phase II will build on this success by developing these models into a complete gear life analysis, including a comprehensive graphical user interface for model construction and analysis control. Extensive verification of the models will ensure accuracy of the results. The completed software will provide analysts with a tool to predict the life of helicopter spiral bevel gears... Award Details


Agency:
Department of Defense
Phase:
Phase II

Gearbox Load and Life Simulation Software

Gear tooth surface fatigue (pitting) is common precursor failure mode that leads to excessive gear vibration, liberation of debris particles that damage ancillary components (e.g. bearings), and serves as crack initiation sites that lead to eventual catastrophic tooth failure. Current gearbox life estimation techniques commonly underplay the significance of gear tooth surface fatigue due to the complexity of the phenomenon involved. The Phase I program successfully demonstrated the feasibility of utilizing advanced modeling techniques to predict the onset and propagation of surface fatigue in gearing, including a rigorous analysis of misalignment, mixed-elastohydrodynamic lubrication, and damage accumulation in the material. Phase II will build on this success by applying these models to a complete gearbox, including a comprehensive graphical user interface for model construction and analysis control. Extensive verification of the models will ensure accuracy of the results. The completed software will provide analysts with a tool to predict the current damage state in helicopter gearboxes and evaluate remaining useful life for anticipated mission profiles... Award Details


Agency:
Department of Defense
Phase:
Phase I

Spline Health Prognosis via Physics Based Modeling Coupled with Component Level Tests

Sentient will develop enhanced fretting fatigue analysis software with rigorous consideration of surface roughness effects in the stick/slip phenomena and fatigue. This will be coupled with an analysis of the stresses and resulting degradation in the material. Sentient will utilize diagnostic data in the form of vibration measurements and/or measured shaft torque to determine the loading conditions and damage progression at the contact. This technology will provide advanced remaining useful life estimates for spline shaft for rotorcraft and other applications... Award Details