MDS-C
Featured Products
  • Reduce prototyping costs and time to market
  • Improve performance and safety
  • Requires fewer experiments than a convertional phenomenological approach
Aerospace
Featured Products
  • Analyzes coupled multiple physical processes at multiple scales
  • Coupled diffusion-reaction-deformation processes
  • Coupled electro-mechanical processes
Environment
Featured Products
  • Computes optimal microstructure based on manufacturing constraints and user-defined optimization criterion
  • Possible optimization criteria: strength and ductility
Benefits
Featured Products
  • Propagates uncertainty at the microscale to the product scale
  • Identifies uncertainty at the microscale based on the scatter in the experimental data at the coupon level
Benefits
Featured Products
  • Free of phenomenological Paris-like fatigue laws
  • Based on multiple temporal scale analysis
  • Experimentally validated
Benefits
Featured Products
  • Translates atomistic information into thermo-mechanical constitutive equation
  • Based on the Generalized Mathematical Homogenization (GMH) theory

MDS, LLC is focused on the creation of practical yet rigorous tools for seamless integration of engineering modeling, simulation, testing and optimization of products involving multiple spatial and temporal scales.

MDS, LLC features product, Multiscale Design System for linking Continuum scales (MDS-C), is a plug-in to commercial finite element software (ABAQUS Standard, ABAQUS Explicit, ANSYS, LS –DYNA) that provides practical yet rigorous and validated multiscale capabilities to commercial codes. MDS has its own parallel nonlinear macro-solver (MDS-MACRO) that can be used as an alternative to commercial finite element codes.

While a good number of multiscale software frameworks (stand alone or plug-ins) already exist (Helius from Firehole, MAC/GMC from NASA, CZone from Engenuity, DIGIMAT from eXstream Engineering), MDS-C provides unmatched combination of practicality, mathematical rigor, verifiability and versatility:

Practicality   

    • MDS-C is equipped with a systematic model reduction technology that reduces complex unit cells having hundreds of thousands of finite elements to a manageable number of deformation modes and state variables. The optimal kinematics (modes/state variables) is automatically selected to provide desired level of accuracy in quantities of interest.

    • MDS-C is equipped with an extensible library of parametric unit cell models generated automatically using MDS built-in CAD and meshing tools. Current library of parametric unit cell models includes fibrous, particulate, woven, fabric and random microstructures. This eliminates the overhead in generating complex unit cells and their linkage to the coarse-scale finite element engines. In addition to parametric library, unit cell models (CAD and/or meshes) can be either imported or generated entirely in MDS.

Mathematical RigorConcept

    • MDS-C is free of scale separation assumption inherent to competing multiscale products. The characteristic material length scale is identified by MDS-C based on user-specified experimental data at a coupon level. MDS-C provides mesh insensitive results at a component and micro levels.

    • MDS-UQ is equipped with stochastic multiscale capabilities that translate geometrical and material uncertainties into component level uncertainties.

Validation

    • MDS-C is integrated with an experimental material database and a multi-step optimization engine that identifies model parameters having high degree of uncertainty (such as content of voids, micro-cracks, interface/interphase properties).

Versatility

    • MDS-OP, MDS-FT, MDS-MP modules provide microstructural optimization, multiscale fatigue and multiphysics capabilities.

MDS-C alone is licensed as MDS-Standard.

MDS-C, MDS-UQ, MDS-FT, MDS-MP is licensed as MDS-Professional.







 


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MDS Version 3.0 released

New MDS features in v3.0 also include:

  • Enhanced physics-based multiscale fatigue
  • Expanded library of parametric unit cell models
  • Improved robustness and accuracy
  • New stochastic multiscale features